A method for adjusting communication of heterogeneous devices

Abstract

The embodiment of the present invention discloses a method for adjusting communication of heterogeneous devices. The method includes: obtaining antenna gain and transmission power of heterogeneous devices in the power system, and the propagation distance between the first sub-device and the second sub-device in the heterogeneous devices, and determining the target path loss value between the first sub-device and the second sub-device according to the antenna gain, transmission power and propagation distance; obtaining the communication data flow between the first sub-device and the second sub-device, and determining the abnormal flow from the communication data flow according to the target path loss value, and determining the device node corresponding to the abnormal flow; determining the cache capacity of the device node, and determining the transmission adjustment path according to the cache capacity, and adjusting the node path of the device node used for communication to the transmission adjustment path. The technical solution of the embodiment of the present invention improves the effectiveness of heterogeneous device communication.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of electric power technology, and in particular to a method for adjusting communication of heterogeneous devices. Background Art

[0002] In power systems, the widespread use of heterogeneous devices has led to an increasing demand for communication among heterogeneous devices.

[0003] However, with the increasing complexity of heterogeneous device communications, it is currently difficult to ensure the effectiveness of heterogeneous device communications, which needs to be urgently addressed. Summary of the invention

[0004] The embodiment of the present invention provides a method for adjusting communication between heterogeneous devices, thereby improving the effectiveness of communication between heterogeneous devices.

[0005] According to one aspect of the present invention, a method for adjusting communication between heterogeneous devices is provided, which may include:

[0006] Obtaining antenna gain and transmit power of heterogeneous devices in the power system, and a propagation distance between a first sub-device and a second sub-device in the heterogeneous devices, and determining a target path loss value between the first sub-device and the second sub-device according to the antenna gain, transmit power, and propagation distance;

[0007] Acquire the communication data flow between the first sub-device and the second sub-device, determine the abnormal flow from the communication data flow according to the target path loss value, and determine the device node corresponding to the abnormal flow;

[0008] The cache capacity of the device node is determined, and according to the cache capacity, a transmission adjustment path is determined, and a node path used for communication of the device node is adjusted to the transmission adjustment path.

[0009] The technical solution of the embodiment of the present invention is to obtain the antenna gain and transmission power of the heterogeneous device in the power system, and the propagation distance between the first sub-device and the second sub-device in the heterogeneous device, and determine the target path loss value between the first sub-device and the second sub-device according to the antenna gain, transmission power and propagation distance, so as to determine the loss of heterogeneous device communication; obtain the communication data flow between the first sub-device and the second sub-device, determine the abnormal flow from the communication data flow according to the target path loss value, and determine the device node corresponding to the abnormal flow to determine the device node with abnormal flow; determine the cache capacity of the device node, and determine the transmission adjustment path according to the cache capacity, and adjust the node path of the device node used for communication to the transmission adjustment path, so as to adjust the node path that affects the effectiveness of heterogeneous device communication. The above technical solution can determine the device node corresponding to the abnormal flow that affects the effectiveness of heterogeneous device communication through the target path loss value, and adjust the node path of the device node used for communication to avoid the influence of abnormal communication between device nodes on heterogeneous device communication, thereby improving the effectiveness of heterogeneous device communication.

[0010] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0012] Figure 1 is a flow chart of a heterogeneous device communication adjustment method provided according to an embodiment of the present invention;

[0013] Figure 2 It is a flowchart of determining a primary and backup path in a heterogeneous device communication adjustment method provided in an embodiment of the present invention;

[0014] Figure 3 is a flow chart of another heterogeneous device communication adjustment method provided according to an embodiment of the present invention;

[0015] Figure 4 is a flow chart of another heterogeneous device communication adjustment method provided according to an embodiment of the present invention;

[0016] Figure 5It is a flow chart of updating a propagation attenuation constant in another heterogeneous device communication adjustment method provided in an embodiment of the present invention;

[0017] Figure 6 is a flow chart of another heterogeneous device communication adjustment method provided according to an embodiment of the present invention;

[0018] Figure 7 is a flowchart of an optional example of another heterogeneous device communication adjustment method provided in an embodiment of the present invention;

[0019] Figure 8 is a structural block diagram of a heterogeneous device communication adjustment device provided according to an embodiment of the present invention;

[0020] Fig. 9 It is a structural schematic diagram of an electronic device for implementing the heterogeneous device communication adjustment method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0021] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0022] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. The situations of "target", "original", etc. are similar and will not be repeated here. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0023] Figure 1 1 is a flowchart of a heterogeneous device communication adjustment method provided in an embodiment of the present invention. This embodiment is applicable to the case of heterogeneous device communication adjustment. The method can be executed by a heterogeneous device communication adjustment device provided in an embodiment of the present invention, and the device can be implemented by software and / or hardware. The device can be integrated in an electronic device, and the electronic device can be various user terminals or servers.

[0024] See also Figure 1 The method of the embodiment of the present invention specifically includes the following steps:

[0025] S110. Obtain antenna gain and transmission power of heterogeneous devices in the power system, and a propagation distance between a first sub-device and a second sub-device in the heterogeneous devices, and determine a target path loss value between the first sub-device and the second sub-device based on the antenna gain, transmission power, and propagation distance.

[0026] Among them, heterogeneous devices are hardware devices of different types, brands, architectures or technical specifications used in the power system. Antenna gain is the ratio of the radiation intensity of the antenna in the heterogeneous device in a specific direction to that of the ideal omnidirectional antenna. Transmit power refers to the average power level output from the transmitter in the heterogeneous device to the antenna. The first sub-device and the second sub-device are both sub-devices in the heterogeneous device. The propagation distance is the distance between the first sub-device and the second sub-device for communication propagation between the first sub-device and the second sub-device. The target path loss value refers to the actual value of the signal strength attenuation caused by the increase in spatial distance during the propagation of the communication signal between the first sub-device and the second sub-device.

[0027] It should be noted that heterogeneous devices may include at least one of a transmitting electronic device, a transforming electronic device, a transmission electronic device, and a communication sub-device, etc. Accordingly, the first sub-device may be a transmitting electronic device, a transforming electronic device, a transmission electronic device, or a communication sub-device, etc., and the second sub-device may be a transmitting electronic device, a transforming electronic device, a transmission electronic device, or a communication sub-device, etc. For example, the first sub-device may be a transmitting electronic device, and the second sub-device may be a communication sub-device.

[0028] It is understandable that in order to ensure the effectiveness and real-time performance of communication between heterogeneous devices, the signal transmission performance and its influencing factors of heterogeneous devices can be studied in depth. Therefore, the target path loss value between the first sub-device and the second sub-device can be determined based on the antenna gain, transmission power and propagation distance.

[0029] In the embodiment of the present invention, the antenna gain can be measured by the standard gain antenna comparison method, and the transmission power can be directly obtained by a power meter. For example, when the first sub-device is a power generation device, when the output power of the power generation device is 30dBm, the signal receiving power after a propagation distance of 1000 meters is about -85dBm. In the embodiment of the present invention, the method for obtaining the antenna gain and transmission power of heterogeneous devices in the power system is not specifically limited.

[0030] In an embodiment of the present invention, for example, a signal propagation delay record between a first sub-device and a second sub-device may be obtained based on a time domain reflectometry method, and a propagation distance may be extracted from the signal propagation delay record. In an embodiment of the present invention, there is no specific limitation on the method for obtaining the propagation distance. It should be noted that the time domain reflectometry method determines the propagation distance by measuring the delay of a high-frequency pulse signal transmitted between a first sub-device and a second sub-device. In a typical application scenario, the distance between the first sub-device and the second sub-device is between 500 meters and 2000 meters, and the signal transmission delay is in the range of 1.67 microseconds to 6.67 microseconds. The sampling rate of the time domain reflectometer is set to 250MHz to meet the measurement accuracy requirements.

[0031] In the embodiment of the present invention, there is no specific limitation on the manner of determining the target path loss value between the first sub-device and the second sub-device according to the antenna gain, the transmission power and the propagation distance.

[0032] S120, obtaining the communication data flow between the first sub-device and the second sub-device, determining abnormal flow from the communication data flow according to the target path loss value, and determining the device node corresponding to the abnormal flow.

[0033] The communication data flow is the data flow of the communication transmission between the first sub-device and the second sub-device. The abnormal flow is the flow in the communication data flow that may cause problems such as blocking of heterogeneous device communication. The device node is the node that generates or produces the abnormal flow.

[0034] In the embodiment of the present invention, a traffic detection tool can be used to collect the communication data flow between the first sub-device and the second sub-device in real time according to the link bandwidth and data packet size between the first sub-device and the second sub-device. For example, a fixed time window can be adaptively set according to the link bandwidth value and the data packet size, and a traffic probe can be used to periodically collect port data packets according to the fixed time window, and the port data packets are used as the communication data flow. In the embodiment of the present invention, the method for obtaining the communication data flow between the first sub-device and the second sub-device is not specifically limited.

[0035] Exemplarily, the proportion of data traffic of different transmission protocol types in the communication data traffic can be analyzed; the actual signal transmission strength between the first sub-device and the second sub-device can be determined; based on the data traffic proportion, the actual signal transmission strength, and the determined numerical range of the channel fading index of the heterogeneous device, the abnormal traffic that causes network congestion can be identified from the communication data traffic, and the device node that generates the abnormal traffic can be located. In the embodiment of the present invention, there is no specific limitation on the method of determining the abnormal traffic from the communication data traffic according to the target path loss value, and determining the device node corresponding to the abnormal traffic.

[0036] In the embodiment of the present invention, a random forest classifier can be used for abnormal traffic to construct a feature vector, and the routing table information and the device topology diagram can be combined to determine the abnormal source node identifier, and the node corresponding to the abnormal source node identifier is used as the device node. In the embodiment of the present invention, the method for determining the device node corresponding to the abnormal traffic is not specifically limited.

[0037] Exemplarily, a random forest classifier can be used to construct a feature vector based on the volatility, duration, buffer status and number of packet losses in the abnormal traffic. Based on the feature vector, a link state table is constructed in combination with the routing table information, and the abnormal source is located by comparing the device topology diagram, and the abnormal source node identifier is determined, and the node corresponding to the abnormal source node identifier is used as the device node. It should be noted that the link state table records the connection relationship and link quality between the first sub-device and the second sub-device. The quality indicators include signal-to-noise ratio and bit error rate. The nodes in the device topology diagram are divided according to the network level, from the core layer, the convergence layer to the access layer. The core layer device abnormality has the largest impact range. The device node is located by tracing back the abnormal traffic transmission path, and the positioning accuracy is improved by combining the statistical results of multiple time windows. In actual applications, the device node positioning accuracy reaches more than 90%, and the positioning delay is controlled within 3 seconds.

[0038] S130, determining the cache capacity of the device node, and determining the transmission adjustment path according to the cache capacity, and adjusting the node path used for communication of the device node to the transmission adjustment path.

[0039] The cache capacity may be the cache usage of the device node. The transmission adjustment path is a path that is required to be adjusted to a node path. The node path is a path used by the device node for communication.

[0040] In the embodiment of the present invention, the queue length and response time parameters of the device node can be recorded according to the cache monitor of the device node, and the cache usage data of the device node can be collected through a fixed time window according to the queue length and response time parameters as the cache capacity. In the embodiment of the present invention, the method for determining the cache capacity of the device node is not specifically limited.

[0041] In the embodiment of the present invention, there is no specific limitation on the manner of determining the transmission adjustment path according to the cache capacity and adjusting the node path of the device node used for communication to the transmission adjustment path.

[0042] In an embodiment of the present invention, the queue growth rate can be calculated according to the cache capacity to obtain the node congestion state value; a bandwidth detector is used to measure the bandwidth of each backup path, and the path quality score of each backup path in the load balancing table is determined according to the round-trip delay and packet loss rate obtained in the bandwidth measurement record; for each backup path, the path quality score and the node congestion state value of the backup path are processed by a feedforward neural network to obtain the data packet priority attribute of the backup path; if the data packet priority attribute of the backup path meets the priority attribute threshold, it is added to the generated data diversion table containing the load ratio; the backup paths with the highest priority are obtained from the data diversion table as the transmission adjustment paths; multi-path planning is performed on each transmission adjustment path by a genetic algorithm, and the main path and the backup path are determined according to the path quality scores corresponding to each transmission adjustment path; according to the main path and the backup path, the node path of the device node for communication is adjusted.

[0043] For example, see Figure 2 , regularly collect cache capacity; calculate queue growth rate and obtain node congestion status value; measure bandwidth of each backup path and record indicators; calculate path quality score; process path quality score and node congestion status value through feedforward neural network; if the data packet priority attribute of the backup path meets the priority attribute threshold, add it to the data diversion table; obtain the transmission adjustment path with the highest priority; plan the path through genetic algorithm and determine the primary and backup paths, that is, determine the primary path and the backup path.

[0044] Exemplarily, the queue growth rate can be calculated based on the cache capacity using the cache access rate; the congestion state value of the device node in the current time window can be determined based on the queue growth rate and the preset congestion threshold; a bandwidth detector can be used to perform periodic bandwidth measurement on each preset backup path, and the round-trip delay and packet loss rate in the bandwidth measurement record can be obtained; a load balancing table can be constructed based on the congestion state value, each backup path, the bandwidth measurement record, and the link state table, and a valid path group that meets the bandwidth demand can be extracted from the load balancing table; a quality score is given to each backup path in the valid path group according to the round-trip delay and packet loss rate corresponding to each backup path in the valid path group, and a path quality score of each backup path in the load balancing table can be obtained; the load balancing table can be updated according to the path quality score of each backup path. The invention discloses a load balancing table; through a feedforward neural network, the quality scores and congestion status values ​​of each path recorded in the load balancing table are processed to obtain the data packet priority attribute of the backup path; if the data packet priority attribute of the backup path meets the priority attribute threshold, it is added to the generated data diversion table containing the load ratio; according to the preset convergence time period, the routing table items are updated; the transmission adjustment paths with the highest priority are obtained from the data diversion table; multi-path planning is performed on the marked data packets in the valid path group through the genetic algorithm, the main path and the backup path are determined according to the path quality scores corresponding to each transmission adjustment path, and the marked data packets are distributed to the corresponding transmission adjustment paths according to the load ratio within the routing table update cycle, so as to adjust the node path of the device node for communication.It should be noted that cache monitoring uses a fixed time window mechanism with a window size of 100 milliseconds. Each window records two key indicators: queue length and response time. Queue length reflects cache usage. When queue length exceeds 80% of cache capacity, congestion warning is triggered. When it exceeds 90%, it is considered to be in a congested state. Response time refers to the time a data packet stays in the cache. Under normal working conditions, the response time is between 1 and 5 milliseconds. When it exceeds 10 milliseconds, it indicates that the node is congested. The queue growth rate is calculated by the change in queue length in adjacent time windows. When the growth rate continues to exceed 50%, it is considered to be congested. The congestion is aggravated; bandwidth detection is achieved by periodically sending detection packets, the detection cycle is 1 second, and 10 detection packets are sent each time; the round-trip delay reflects the path transmission performance. In the metropolitan area network environment, the normal delay is less than 5 milliseconds and the packet loss rate is less than 0.1%; the link state table records the bandwidth utilization, delay jitter and queue status of each path. Paths with bandwidth utilization exceeding 80% are not included in the valid path group; the path quality score is calculated by weighted calculation, with a delay weight of 0.4, a packet loss weight of 0.3, and a bandwidth utilization weight of 0.3. The score is standardized between 0 and 100; feedforward neural network It contains a 3-layer structure. The number of nodes in the input layer is 8, corresponding to the characteristic parameters of the path quality score and congestion status. The hidden layer uses 16 nodes, and the output layer generates data diversion decisions. The data packets are prioritized according to the business type and transmission time. The priority of key business data packets is 1, and the priority of ordinary data packets is 2 to 4. The load ratio is calculated based on the path quality score. Paths with high scores are allocated a larger proportion of traffic. The maximum load ratio of a single path does not exceed 40%. The routing table update cycle is set to 2 seconds to ensure network convergence. The genetic algorithm performs path planning for marked data packets, and the population size is set is 50, and the evolutionary generation is 100; the chromosome encoding includes two parts: path sequence and load ratio, and the path selection is optimized through crossover and mutation operations; the primary path selects the path with the highest quality score, and the backup path selects the path with the second highest score and no overlapping links with the primary path; the path switching adopts soft switching, and the traffic is gradually migrated after the new path is established. The migration cycle is 200 milliseconds to avoid traffic mutation; in actual applications, this solution disperses the traffic to 3 to 5 backup paths when the node is congested, reducing the load of the congested node by 40% to 60%, and the network recovery time is controlled within 5 seconds.

[0045] In an embodiment of the present invention, after the node path of the device node used for communication is adjusted to a transmission adjustment path, that is, after the load balancing of the abnormal traffic is completed, the communication data traffic change trend between the first sub-device and the second sub-device can be continuously detected, and a curve graph of the communication data traffic change trend is drawn based on the obtained change trend. According to the curve graph, the node path of the device node used for communication is dynamically adjusted to maintain the network in a preset stable state.

[0046] In an embodiment of the present invention, after the node path of the device node used for communication is adjusted to a transmission adjustment path, that is, after the load balancing of the abnormal traffic is completed, the communication data traffic of the link between the first sub-device and the second sub-device can also be collected, and the upper threshold of the traffic fluctuation rate and the lower threshold of the traffic fluctuation rate are obtained according to the communication data traffic. According to the upper threshold of the traffic fluctuation rate and the lower threshold of the traffic fluctuation rate, a real-time traffic curve is generated; a bidirectional gated recurrent neural network is used for time series feature learning, and the time series features are trained through a sliding time window to obtain a traffic prediction model; according to the real-time traffic curve, a predicted traffic curve is obtained through the traffic prediction model, and a gradient boosting tree is used to extract the traffic balancing features and path quality features in the predicted traffic curve, and the routing adjustment weight is calculated according to the traffic balancing features, the path quality features and the throughput mean between the first sub-device and the second sub-device; if the routing adjustment weight deviates from the stable threshold, the traffic parameter for communication between the first sub-device and the second sub-device is error corrected.

[0047] Exemplarily, after the node path of the device node used for communication is adjusted to a transmission adjustment path, the traffic monitor of the link between the first sub-device and the second sub-device collects the communication data traffic every second, and records the mean and standard deviation of the data packet throughput; the upper and lower thresholds of the traffic fluctuation rate are set based on historical data; a sliding time window mechanism is used to generate a real-time traffic curve based on the collected communication data traffic, the mean and the standard deviation, and the node traffic distribution confidence interval is marked on the real-time traffic curve according to the upper and lower thresholds of the traffic fluctuation rate; a data sequence with a sliding window size of 60 seconds is used to train a traffic prediction model composed of a bidirectional gated recurrent neural network, and the real-time traffic curve is subjected to time series feature learning through the bidirectional gated recurrent neural network, and the traffic curve containing timestamps, The real-time traffic curve of throughput and volatility is used for feature extraction to generate a predicted traffic curve with a confidence interval; the gradient boosting tree is used to extract traffic balancing features and path quality features from the predicted traffic curve, and the routing adjustment weight is calculated according to the traffic balancing features, path quality features, throughput mean, volatility and link saturation; an anti-oscillation traffic adjustment table is constructed based on the network convergence time and path switching cycle, and according to the anti-oscillation traffic adjustment table, the error correction is performed on the traffic parameters of the communication between the first sub-device and the second sub-device that deviate from the stable threshold; through the path adjustment weight, a set of alternative paths is generated, and the paths in the set of alternative paths are sorted according to the convergence speed priority, and according to the sorting result, the traffic migration is performed within the preset adjustment period.It should be noted that traffic monitoring uses a sampling period of seconds to record the throughput and fluctuation characteristics of data packets; on a 100-megabit link, the average throughput under normal working conditions fluctuates between 40 and 60 megabits per second, with a standard deviation of less than 5 megabits per second; historical data statistics show that network performance begins to decline when the traffic fluctuation rate exceeds 30%, and congestion occurs when it exceeds 50%; the sliding window adopts a width of 60 seconds and slides once per second to keep the latest traffic change trend; the confidence interval is set to 95% to determine whether the communication data traffic volume is within the normal range; the bidirectional gated recurrent neural network consists of two parts, an encoder and a decoder. The encoder processes historical traffic data and the decoder generates prediction results; the network structure adopts a 3-layer design, each layer contains 128 hidden units; the input features include three dimensions: timestamp, throughput, and volatility, and the time features consider hourly periodicity and daily periodicity; the training data is prepared in a sliding window manner, using the data of the most recent hour to predict the traffic in the next 5 minutes; the predicted traffic curve contains expected values ​​and confidence intervals, and the confidence interval reflects the uncertainty of the prediction; the traffic balancing features extracted by the gradient boosting tree include the uniformity, stability and Symmetry; Uniformity is measured by calculating the standard deviation of traffic at each node. A standard deviation less than 10% of the total traffic indicates uniform distribution; Stability is evaluated based on the traffic change rate. A change rate less than 20% is considered stable; Symmetry reflects the balance of upstream and downstream traffic. A ratio between 0.8 and 1.2 is normal; Path quality features include bandwidth utilization, latency, and packet loss rate, with weights of 0.4, 0.3, and 0.3, respectively; Route adjustment weights are calculated based on these features; Anti-oscillation traffic regulation adopts a progressive adjustment strategy, with a single adjustment range not exceeding 20% ​​of the current traffic; Network reception The convergence time is usually 2 to 3 seconds, and the path switching cycle is set to 5 seconds to ensure that the network is stable before making the next adjustment; the alternative paths are sorted according to quality, and the quality score takes into account three aspects: bandwidth redundancy, delay stability, and historical reliability; traffic migration adopts soft switching, first establishing a new path and verifying its performance, and then gradually migrating traffic from the old path to the new path. The migration process lasts 10 to 15 seconds; practice has shown that this solution can control network fluctuations within the preset threshold range, keep the throughput stable within plus or minus 5% of the target value, and avoid performance jitter caused by frequent path switching.

[0048] The technical solution of the embodiment of the present invention is to obtain the antenna gain and transmission power of the heterogeneous device in the power system, and the propagation distance between the first sub-device and the second sub-device in the heterogeneous device, and determine the target path loss value between the first sub-device and the second sub-device according to the antenna gain, transmission power and propagation distance, so as to determine the loss of heterogeneous device communication; obtain the communication data flow between the first sub-device and the second sub-device, determine the abnormal flow from the communication data flow according to the target path loss value, and determine the device node corresponding to the abnormal flow to determine the device node with abnormal flow; determine the cache capacity of the device node, and determine the transmission adjustment path according to the cache capacity, and adjust the node path of the device node used for communication to the transmission adjustment path, so as to adjust the node path that affects the effectiveness of heterogeneous device communication. The above technical solution can determine the device node corresponding to the abnormal flow that affects the effectiveness of heterogeneous device communication through the target path loss value, and adjust the node path of the device node used for communication to avoid the influence of abnormal communication between device nodes on heterogeneous device communication, thereby improving the effectiveness of heterogeneous device communication.

[0049] An optional technical solution determines abnormal traffic from communication data traffic based on a target path loss value, including: analyzing the communication data traffic to obtain the data traffic proportion corresponding to at least one communication protocol; determining abnormal traffic from the communication data traffic based on the data traffic proportion corresponding to at least one communication protocol and the target path loss value.

[0050] The communication protocol is the communication protocol used for communication between the first sub-device and the second sub-device. The data flow ratio is the ratio of the data flow using the corresponding communication protocol to the communication data flow.

[0051] In an embodiment of the present invention, a transmission protocol analyzer can be used to analyze communication data traffic to obtain a data traffic proportion corresponding to at least one communication protocol and a protocol data stream corresponding to at least one communication protocol. According to the data traffic proportion corresponding to at least one communication protocol, the protocol data stream corresponding to at least one communication protocol is classified and counted to obtain a basic traffic feature sequence; according to the arrival timestamp of the data packet in the basic traffic feature sequence, the buffer storage state of the heterogeneous device is determined through a buffer sampler; the number of packet losses is counted using a data packet sequence number tracker, and the number of packet losses is weighted according to the channel fading index to obtain an enhanced traffic feature sequence; the traffic fluctuation rate and fluctuation duration in the enhanced traffic feature sequence are calculated by a traffic fluctuation detector, and the upper limit of the data packet delay is calculated according to the actual signal transmission strength; based on the traffic fluctuation rate, fluctuation duration, preset fluctuation rate threshold, duration threshold and delay upper limit, the traffic data packets that cause network congestion in the communication data traffic are extracted to form a congested traffic feature sequence, and the congested traffic feature sequence is used as abnormal traffic. In an embodiment of the present invention, the communication data traffic is analyzed to obtain a method for the data traffic ratio corresponding to at least one communication protocol, and a method for determining abnormal traffic from the communication data traffic based on the data traffic ratio corresponding to at least one communication protocol and a target path loss value is not specifically limited.

[0052] Exemplarily, the communication data flow can be analyzed by a transport protocol analyzer, the protocol data flows corresponding to the transport layer protocol and the application layer can be distinguished, the protocol data flows in each time window can be classified and counted, and the bandwidth occupancy rate of the unit window can be calculated in combination with the link bandwidth according to the classification and counting results to generate a basic traffic feature sequence; a data packet parser can be used to record the arrival timestamps of the data packets in the basic traffic feature sequence, and the buffer storage status of the heterogeneous device can be detected in real time through a buffer sampler to obtain the adopted detection data, and the buffer storage status curve can be extracted from the adopted detection data; the number of packet losses can be counted by a data packet sequence number tracker, and the number of packet losses can be weighted according to the channel fading index, and an enhanced traffic feature sequence can be generated according to the holiday calculation results and the buffer storage status curve; the traffic fluctuation rate and fluctuation duration in the enhanced traffic feature sequence can be calculated by a traffic fluctuation detector, and the upper limit of the data packet delay can be calculated according to the actual signal transmission strength, and the traffic data packets that cause network congestion in the communication data flow can be extracted according to the traffic fluctuation rate, fluctuation duration, preset fluctuation rate threshold, duration threshold and delay upper limit to form a congested traffic feature sequence, and the congested traffic feature sequence can be used as abnormal traffic.It should be noted that data flow detection adopts a fixed time window sampling method. The window size is related to the link bandwidth and data packet size. For a 100-megabit link, when the typical data packet size is 1500 bytes, the sampling window is set to 100 milliseconds. The transport layer protocol mainly includes the Transmission Control Protocol and the User Datagram Protocol, and the application layer protocol includes the File Transfer Protocol, the Remote Login Protocol and the Simple Network Management Protocol. The protocol identification field is used to distinguish different types of data streams. The bandwidth occupancy rate is calculated based on the byte count within the unit time window. Under normal working conditions, the bandwidth occupancy rate fluctuates between 20% and 60%. The data packet timestamp recording accuracy reaches the microsecond level, which is used to calculate the arrival time interval between data packets. The device buffer status detection adopts periodic sampling at an interval of 10 milliseconds to record the percentage of buffer usage in the total capacity. The data packet sequence number is continuously tracked. When the sequence number is detected to be discontinuous, it is determined to be a packet loss, and the location and number of packet losses are recorded. Channel fading index When the fading index is between 2 and 4, the weighting coefficient of the number of packet losses is 1.2 to 1.8, and when the fading index is greater than 4, the weighting coefficient exceeds 2; the buffer status curve reflects the degree of data backlog, and it enters the warning state when the utilization rate continues to exceed 80%; the flow fluctuation detection is based on the flow change rate of adjacent time windows, the normal business flow change rate is within 30%, and the fluctuation duration is less than 500 milliseconds; when the signal transmission strength decreases, the upper limit of the data packet delay increases accordingly, and the upper limit of the delay is 100 milliseconds at -75 decibel milliwatts, and increases to 200 milliseconds at -85 decibel milliwatts; the abnormal flow judgment criteria include: flow fluctuation rate exceeds 50%, fluctuation duration exceeds 1 second, or buffer utilization rate exceeds 90% for 300 milliseconds; the random forest classifier uses 64 decision trees, and the input feature vector contains 8 dimensions: flow fluctuation rate, fluctuation duration, average buffer utilization, buffer peak utilization, packet loss rate, average delay, maximum delay and minimum delay.

[0053] In an embodiment of the present invention, it is also possible to simulate the network transmission process under different channel fading indexes within a numerical range, obtain statistical results of various network performance indicators, analyze the statistical results, judge the degree of influence of channel fading on network congestion based on the analysis results, determine the parameter relationship between the fading parameters and the network performance indicators based on the degree of influence, and determine abnormal traffic from the communication data traffic based on the parameter relationship, the data traffic proportion corresponding to at least one communication protocol, and the target path loss value.

[0054] In an embodiment of the present invention, random fading channel parameters can also be generated according to a numerical interval; using the random fading channel parameters, a channel model including a direct path and a reflected path is generated through a multipath channel modeler; using a long short-term memory neural network to process the channel model, a queue length sequence and a transmission delay sequence are obtained, and a network performance indicator group is obtained as a statistical result according to the queue length sequence and the transmission delay sequence; for the packet loss rate and queue length in the statistical results, a congestion degree score is calculated, and according to the congestion degree score, an impact weight data is determined through a cross-validation method; the bandwidth utilization and throughput data are normalized to obtain a network performance curve family; using a support vector machine to extract the congestion critical point features from the network performance curve family, combining the impact weight data to identify the corresponding rules of the congestion critical point features, and obtain a network congestion determination threshold table; according to the network congestion determination threshold table, the data traffic proportion corresponding to at least one communication protocol, and the target path loss value, the abnormal traffic is determined from the communication data traffic.

[0055] Exemplarily, according to the numerical interval, the fading parameter sampling interval is set according to the Nyquist sampling theorem, and according to the fading parameter sampling interval, a multipath channel modeler is used to generate a channel model including a direct path and a reflected path; a test data stream with specified burstiness and duration characteristics is generated through a traffic generator; through the channel model, the queue length, transmission delay and throughput data of the test data stream under different fading parameters are recorded; a long short-term memory neural network is used to process the dynamic change sequence of queue length and transmission delay, and according to the burstiness and duration of the test data stream, the burst aggregation of the data packet stream is calculated, and the transmission delay jitter amplitude is counted, and a network performance indicator group is extracted from the processed queue length and transmission delay, burstiness, duration, burst aggregation and transmission delay jitter amplitude, and a bandwidth is constructed according to the network performance indicator group and throughput data. A time series mapping table of utilization and throughput; based on the packet loss rate and queue length in the network performance indicator group, a congestion degree score is calculated; according to the congestion degree score, a cross-validation method is used to calculate the influence weight of the fading parameter to obtain the influence weight data; the data points in the time series mapping table are normalized to the maximum and minimum values ​​to generate a network performance curve family; the congestion critical point in the network performance curve family is feature extracted by a support vector machine to obtain the congestion critical point feature; according to the congestion critical point feature, combined with the delay jitter value of adjacent data packets and the queue length, the corresponding law of the fading parameter and the network performance indicator is identified from the influence weight data to obtain the network congestion determination threshold table; according to the network congestion determination threshold table, the data flow proportion corresponding to at least one communication protocol and the target path loss value, the abnormal flow is determined from the communication data flow.It should be noted that the fading parameters are sampled according to the Nyquist theorem. In the range of fading exponents 2 to 4, the sampling interval is 0.2, and 11 discrete sampling points are obtained. The multipath channel contains 1 direct path and 2 to 3 reflected paths. The relative delay of the reflected path is between 0.1 and 2 microseconds, and the relative power is 5 to 20 decibels lower than that of the direct path. The burst characteristics of the test data stream are described by the duty cycle. The burst period is set to 100 milliseconds, the duty cycle varies between 20% and 80%, and the duration of a single burst is 20 to 80 milliseconds. The queue length is set to an upper limit of 1000 data packets, and the transmission delay measurement is The accuracy is in microseconds; the long short-term memory neural network adopts a two-layer structure, each layer contains 128 neurons, and the input feature dimension is 4, including queue length, transmission delay, packet interval and burst duration; the burst aggregation of the packet flow is defined as the ratio of the number of burst packets to the average number of packets per unit time, and this ratio is between 1.5 and 3 under normal working conditions; the transmission delay jitter describes the degree of change in the delay difference between adjacent packets, which is obtained by calculating the standard deviation of the delay sequence, and the typical value is between 1 and 5 milliseconds; the bandwidth utilization is recorded every 100 milliseconds to form a corresponding relationship with the throughput ; The congestion degree score is calculated based on the normalized indicator values, with the packet loss rate weighted as 0.4, the queue length weighted as 0.3, and the delay weighted as 0.3; the 5-fold cross-validation method is used to calculate the impact weight data of the fading parameters, and the validation set accounts for 20% of the total data volume; the normalization process uses the maximum and minimum value method to map each indicator to the range of 0 to 1; the network performance curve family includes throughput curves, delay curves, and packet loss rate curves, and each curve corresponds to a fading parameter value; the support vector machine uses the radial basis kernel function to extract congestion critical features, and the input features include normalized performance indicators and fading parameters The congestion critical point determination criteria are that the queue length exceeds 80% of the capacity, or the packet loss rate exceeds 1%, or the delay jitter exceeds 10 milliseconds; the experimental results show that when the fading index is between 2 and 3, the network performance indicators change smoothly and the probability of congestion is less than 10%; when the fading index is between 3 and 4, the performance indicators deteriorate faster, and the probability of congestion increases exponentially with the increase of the fading index. When the fading index reaches 4, the probability of congestion exceeds 50%; the network congestion determination threshold table is generated according to the critical values ​​of performance indicators under different fading parameters, which is used to detect the network status in real time and predict the risk of congestion.

[0056] In the embodiment of the present invention, by determining abnormal traffic from communication data traffic according to the data traffic proportion and the target path loss value respectively corresponding to at least one communication protocol, the accuracy of the determined abnormal traffic can be improved.

[0057] Another optional technical solution is to determine the transmission adjustment path according to the cache capacity, including: evaluating the congestion level of the device node according to the cache capacity; and determining the transmission adjustment path when the congestion level exceeds a preset level threshold.

[0058] In the embodiment of the present invention, for example, the congestion score of the device node can be determined according to the cache capacity, and the congestion score can be used as the congestion degree of the device node. In the embodiment of the present invention, the method of evaluating the congestion degree of the device node according to the cache capacity is not specifically limited.

[0059] In the embodiment of the present invention, when the congestion level exceeds the preset congestion level threshold, the transmission adjustment path is calculated according to the preset number of backup paths and the routing table update cycle to guide the device node to the transmission adjustment path, so as to adjust the node path used for communication of the device node to the transmission adjustment path, and complete the load balancing of abnormal traffic. In the embodiment of the present invention, the method of determining the transmission adjustment path when the congestion level exceeds the preset congestion level threshold is not specifically limited.

[0060] In an embodiment of the present invention, by determining a transmission adjustment path when the congestion level exceeds a preset level threshold, it is possible to adjust the node path used for communication of the device node to a transmission adjustment path in a relatively congested situation. This not only improves the effectiveness of communication between heterogeneous devices, but also avoids performance jitters caused by frequent path switching in non-congested or slightly congested situations.

[0061] Figure 3 It is a flowchart of another heterogeneous device communication adjustment method provided in an embodiment of the present invention. This embodiment is optimized based on the above-mentioned technical solutions. In this embodiment, optionally, according to the target path loss value, the abnormal traffic is determined from the communication data traffic, including: obtaining the signal frequency parameters of the heterogeneous device, and determining the actual signal transmission strength between the first sub-device and the second sub-device according to the target path loss value and the signal frequency parameter; determining the abnormal traffic from the communication data traffic according to the actual signal transmission strength. Among them, the explanations of the terms that are the same or corresponding to the above-mentioned embodiments are not repeated here.

[0062] See also Figure 3 The method of this embodiment may specifically include the following steps:

[0063] S210. Obtain antenna gain and transmission power of heterogeneous devices in the power system, and a propagation distance between a first sub-device and a second sub-device in the heterogeneous devices, and determine a target path loss value between the first sub-device and the second sub-device based on the antenna gain, transmission power, and propagation distance.

[0064] S220: Obtain the communication data flow between the first sub-device and the second sub-device.

[0065] S230: Acquire signal frequency parameters of the heterogeneous devices, and determine actual signal transmission strength between the first sub-device and the second sub-device according to the target path loss value and the signal frequency parameters.

[0066] The signal frequency parameter is a parameter related to the communication frequency of the signal of the heterogeneous devices. The actual signal transmission strength is the actual signal transmission strength of the signal communicated between the first sub-device and the second sub-device.

[0067] In the embodiment of the present invention, the method for obtaining the signal frequency parameters of the heterogeneous devices is not specifically limited.

[0068] In an embodiment of the present invention, for example, the theoretical signal transmission strength between the first sub-device and the second sub-device can be calculated based on the signal frequency parameter, the target path loss value, and the determined numerical range of the channel fading index; according to the theoretical signal transmission strength and the potential interference source information of the heterogeneous devices within a preset range, the theoretical signal transmission strength is corrected for interference to obtain the actual signal transmission strength. In an embodiment of the present invention, the method for determining the actual signal transmission strength between the first sub-device and the second sub-device based on the target path loss value and the signal frequency parameter is not specifically limited.

[0069] S240: Determine abnormal traffic from communication data traffic according to actual signal transmission strength.

[0070] In the embodiment of the present invention, the method of determining abnormal traffic from communication data traffic according to actual signal transmission strength is not specifically limited.

[0071] S250: Determine the device node corresponding to the abnormal traffic.

[0072] S260: Determine the cache capacity of the device node, and determine the transmission adjustment path according to the cache capacity, and adjust the node path used for communication of the device node to the transmission adjustment path.

[0073] The technical solution of the embodiment of the present invention can improve the accuracy of the determined abnormal traffic by determining the actual signal transmission strength and determining the abnormal traffic from the communication data traffic.

[0074] An optional technical solution determines the actual signal transmission strength between a first sub-device and a second sub-device based on a target path loss value and a signal frequency parameter, including: determining the theoretical signal transmission strength between the first sub-device and the second sub-device based on the target path loss value and the signal frequency parameter; determining potential interference source information of heterogeneous devices within a preset range, and correcting the theoretical signal transmission strength based on the potential interference source information to obtain the actual signal transmission strength between the first sub-device and the second sub-device.

[0075] The theoretical signal transmission strength is the theoretical signal transmission strength of the signal between the first sub-device and the second sub-device. The preset range is a preset range in which the interference source may interfere with the communication between the first sub-device and the second sub-device; the preset range may be, for example, a Fresnel zone space range. The potential interference source information is information related to the interference source within the preset range that may potentially interfere with the communication between the first sub-device and the second sub-device.

[0076] In an embodiment of the present invention, a piecewise linear loss curve can be constructed according to the target path loss value and the signal frequency parameter, and the theoretical signal transmission strength can be obtained by weighted correction of the piecewise linear loss curve according to the signal field strength distribution measured by the field strength meter and the spatial radiation angle parameter measured by the phase array antenna; a spectrum scanner is used to determine the potential interference source information of heterogeneous devices within a preset range; triangulation positioning marking is performed on the potential interference source information, and an interference source characteristic parameter group consisting of the potential interference source information of the interference source whose transmission power is greater than the preset threshold is extracted; if the interference source characteristic parameter group meets the classification condition of the support vector machine, a total interference correction value is calculated according to the frequency selectivity of the interference source and the theoretical signal transmission strength of the signal-to-noise ratio state; spatial attenuation compensation is performed on the total interference correction value, and according to the compensation result, the interference correction amount is calculated through the spatial radiation angle parameter, and the total interference correction value and the interference correction amount are superimposed on the theoretical signal transmission strength to obtain the actual signal transmission strength. In an embodiment of the present invention, there is no specific limitation on the method of determining the theoretical signal transmission strength between the first sub-device and the second sub-device based on the target path loss value and the signal frequency parameter, and determining the potential interference source information of heterogeneous devices within a preset range, and correcting the theoretical signal transmission strength based on the potential interference source information to obtain the actual signal transmission strength between the first sub-device and the second sub-device.

[0077] Exemplarily, a piecewise linear loss curve is constructed according to the target path loss value and the signal frequency parameter, a coverage area map is obtained according to the signal field strength distribution measured by the field strength meter, a phased array antenna is used to measure the spatial radiation angle parameter, and a weighted correction is performed on the piecewise linear loss curve according to the fading index value according to the coverage area map and the spatial radiation angle parameter to obtain a theoretical signal transmission strength; a spectrum scanner is used to scan and record the information of potential interference sources at different time points within a preset range, the interference sources are located and marked based on the triangulation positioning principle, and interference sources with a transmission power greater than a preset threshold are extracted from the marked interference sources, and an interference source map is constructed according to the potential interference source information and the interference sources with a transmission power greater than the preset threshold according to the transmission power level. The interference source power distribution diagram records the link quality index of each interference source, and determines the interference source characteristic parameter group according to the link quality index and the interference source power distribution diagram; the transmission power level, link quality index and interference source position coordinates in the interference source characteristic parameter group are classified into multi-dimensional features through the support vector machine, and the first interference correction amount is calculated according to the frequency selectivity and signal-to-noise ratio state of each interference source, and the first interference correction amount corresponding to all interference sources is accumulated to obtain the total interference correction value; based on the signal field strength distribution, the total interference correction value is compensated for spatial attenuation, and the interference correction amount is calculated in combination with the spatial radiation angle parameter, and the total interference correction value and the interference correction amount are superimposed on the theoretical signal transmission strength, and the actual signal transmission strength is output through the signal-to-noise ratio determiner.It should be noted that the relationship between signal transmission loss and frequency presents a piecewise linear characteristic. In the 2.4GHz band, the loss increases by 6 decibels per octave, while in the 5.8GHz band, the loss increases by 8 decibels. The field strength meter adopts a grid scanning method, and the measurement interval is set to 1 / 4 of the wavelength. The typical value is 3 cm in the 2.4GHz band and 1.3 cm in the 5.8GHz band. The phased array antenna consists of 16 array elements, and the signal arrival angle is measured by electronic scanning. The azimuth angle measurement range is plus or minus 60 degrees, the elevation angle measurement range is plus or minus 30 degrees, and the angular resolution is better than 2 degrees. Interference source location The positioning adopts the principle of triangulation, and three direction-finding stations are arranged in the preset area. Each direction-finding station measures the arrival angle of the interference signal, and determines the coordinates of the interference source through angle intersection. The bandwidth of the spectrum scan covers 2.4 to 5.8 GHz, the scanning step is 100 kHz, and the dwell time is 1 millisecond. The transmission power is divided into four levels according to the intensity: less than 10 milliwatts is low power, 10 to 100 milliwatts is medium power, 100 to 500 milliwatts is medium-high power, and greater than 500 milliwatts is high power. The link quality indicators include two parameters: signal-to-noise ratio and bit error rate. The signal-to-noise ratio threshold is set to 12 decibels, and the bit error rate threshold is set to 0. =10 to the negative sixth power; the support vector machine classifies the interference source features in five dimensions, and the input features include transmission power, signal-to-noise ratio, bit error rate, azimuth and distance; the feature space is constructed by the radial basis kernel function, and the theoretical signal transmission strength of different types of interference sources is calculated; in the 5.8GHz frequency band, the correction introduced by the low-power interference source is 0.5 to 1 decibel, the medium power is 1 to 2 decibels, the medium and high power is 2 to 4 decibels, and the high power exceeds 4 decibels; the frequency selectivity is manifested in the different interference effects at different frequencies, and the correction increases by 1 decibel for every 3 decibel decrease in the signal-to-noise ratio; the spatial attenuation compensation takes into account the interference source and The relative position relationship of the devices, under the condition of free space propagation, the interference impact is reduced by 6 decibels for every doubling of the distance; the spatial radiation angle affects the polarization matching degree of the signal, when the interference source is orthogonal to the polarization direction of the target device antenna, the interference correction amount is minimum; the signal-to-noise ratio judgment adopts a segmented judgment strategy, when the superimposed corrected signal-to-noise ratio is lower than 8 decibels, the transmission power is increased to compensate, when the signal-to-noise ratio is higher than 15 decibels, the transmission power is reduced to reduce interference to other devices; through dynamic adjustment, the transmission strength is ultimately maintained at the minimum level to ensure reliable communication, and the typical value is 3 to 6 decibels higher than the theoretical value of space loss.

[0078] In an embodiment of the present invention, by correcting the theoretical signal transmission strength according to the determined potential interference source information to obtain the actual signal transmission strength between the first sub-device and the second sub-device, the accuracy of the determined actual signal transmission strength can be improved, thereby further improving the accuracy of the determined abnormal traffic.

[0079] Figure 4It is a flowchart of another heterogeneous device communication adjustment method provided in an embodiment of the present invention. This embodiment is optimized based on the above-mentioned technical solutions. In this embodiment, optionally, the target path loss value between the first sub-device and the second sub-device is determined according to the antenna gain, the transmission power and the propagation distance, including: determining the spatial attenuation compensation value between the first sub-device and the second sub-device according to the antenna gain and the transmission power; determining the first path loss value according to the antenna gain and the propagation distance; obtaining the standing wave ratio parameter, and determining the target path loss value between the first sub-device and the second sub-device according to the spatial attenuation compensation value, the first path loss value and the standing wave ratio parameter. Among them, the explanations of the terms that are the same or corresponding to the above-mentioned embodiments are not repeated here.

[0080] See also Figure 4 The method of this embodiment may specifically include the following steps:

[0081] S310: Obtain antenna gain and transmission power of a heterogeneous device in the power system, and a propagation distance between a first sub-device and a second sub-device in the heterogeneous device.

[0082] S320: Determine a spatial attenuation compensation value between the first sub-device and the second sub-device according to the antenna gain and the transmit power.

[0083] The spatial attenuation compensation value is a compensation value for compensating for the natural attenuation of the signal as the propagation distance increases.

[0084] In the embodiment of the present invention, there is no specific limitation on the manner of determining the spatial attenuation compensation value between the first sub-device and the second sub-device according to the antenna gain and the transmit power.

[0085] S330. Determine a first path loss value according to the antenna gain and the propagation distance.

[0086] The first path loss value is a theoretical value of the signal strength attenuation caused by the increase in spatial distance during the propagation of the communication signal between the first sub-device and the second sub-device.

[0087] In an embodiment of the present invention, the beam coupling degree parameter between the first sub-device and the second sub-device can be measured by a standing wave ratio measuring instrument, and the spatial free propagation loss can be calculated according to the propagation distance. The first path loss value can be determined according to the propagation attenuation and the beam coupling degree parameter obtained by the calculation. In an embodiment of the present invention, there is no specific limitation on the method of determining the first path loss value according to the antenna gain and the propagation distance. It should be noted that the standing wave ratio measurement is performed at the transmitting end of the communication between the first sub-device and the second sub-device using a network analyzer. During normal operation, the standing wave ratio value should be less than 1.5, indicating that the antenna is well matched and the beam coupling strength between the devices meets the standard.

[0088] Exemplarily, a standard attenuation calculation formula can be used to identify the signal strength at different geographical locations between the first sub-device and the second sub-device. According to the propagation distance and the spatial free propagation loss calculation formula, the propagation attenuation is calculated, and the signal strength at different geographical locations is compared and measured to obtain the barrier loss rate that will affect the communication between the first sub-device and the second sub-device. According to the beam coupling parameter, the propagation attenuation and the barrier loss rate, the antenna gain is corrected to obtain the first path loss value. It should be noted that the standard attenuation calculation is based on the basic law of free space propagation loss, considering the actual transmission environment between the first sub-device and the second sub-device, and the basic path loss of 107.7dB is generated at a frequency of 5.8GHz for a distance of 1000 meters; the barrier loss rate is specifically obtained by measuring the received signal strength under two conditions of obstruction and non-obstruction, and calculating the difference in signal strength. The loss of common concrete walls at a frequency of 5.8GHz is about 20dB to 30dB.

[0089] It should be noted that the signal beam propagation path involved can be calculated through the Fresnel zone. The radius of the first Fresnel zone in the Fresnel zone is related to the propagation distance and the operating frequency. In the 5.8GHz frequency band, the radius of the first Fresnel zone corresponding to a propagation distance of 1000 meters is 4.5 meters. The spatial range of the Fresnel zone can be used to determine whether there are obstacles. That is, the signal strength of different geographical locations within the spatial range of the Fresnel zone can be compared and measured to obtain the obstacle loss rate.

[0090] S340: Acquire a standing wave ratio parameter, and determine a target path loss value between the first sub-device and the second sub-device according to the spatial attenuation compensation value, the first path loss value, and the standing wave ratio parameter.

[0091] Among them, the standing wave ratio parameter is a parameter that measures the relative strength of the reflected wave and the incident wave in the transmission line or antenna.

[0092] In the embodiment of the present invention, there is no specific limitation on the method of obtaining the standing wave ratio parameter and determining the target path loss value between the first sub-device and the second sub-device according to the spatial attenuation compensation value, the first path loss value and the standing wave ratio parameter.

[0093] S350, obtaining the communication data flow between the first sub-device and the second sub-device, determining abnormal flow from the communication data flow according to the target path loss value, and determining the device node corresponding to the abnormal flow.

[0094] S360: Determine the cache capacity of the device node, and determine the transmission adjustment path according to the cache capacity, and adjust the node path used for communication of the device node to the transmission adjustment path.

[0095] The technical solution of the embodiment of the present invention can avoid the influence of the inaccurate target path loss value on the accuracy of the determined abnormal traffic by determining the target path loss value between the first sub-device and the second sub-device based on the spatial attenuation compensation value, the first path loss value and the standing wave ratio parameter.

[0096] An optional technical solution determines a target path loss value between a first sub-device and a second sub-device based on a spatial attenuation compensation value, a first path loss value, and a standing wave ratio parameter, including: determining a second path loss value between the first sub-device and the second sub-device based on the standing wave ratio parameter, the spatial attenuation compensation value, and the first path loss value; obtaining the link transmission quality of heterogeneous devices, and determining the target path loss value between the first sub-device and the second sub-device based on the standing wave ratio parameter, the link transmission quality, and the second path loss value.

[0097] Among them, the second path loss value is a theoretical value with higher accuracy than the first path loss value, which is a signal strength attenuation caused by the increase in spatial distance during the propagation of the communication signal between the first sub-device and the second sub-device. The link transmission quality is the signal transmission quality of the link between the first sub-device and the second sub-device.

[0098] In an embodiment of the present invention, a support vector regression algorithm may be used to establish a prediction function of a spatial attenuation compensation value and a first path loss value, and the antenna gain may be numerically optimized based on a standing wave ratio parameter and the prediction function to obtain a second path loss value. In an embodiment of the present invention, there is no specific limitation on the method of determining the second path loss value between the first sub-device and the second sub-device based on the standing wave ratio parameter, the spatial attenuation compensation value and the first path loss value. It should be noted that the support vector regression algorithm processes multiple groups of measured data to establish a prediction model of a spatial attenuation compensation value and a first path loss value, that is, the spatial attenuation compensation value and the first path loss value may be multiple groups, and the input variables of the prediction model may include at least one of the parameters such as antenna gain, propagation distance, operating frequency and standing wave ratio, and outputs a corrected second path loss value.

[0099] In the embodiment of the present invention, the antenna gain may also be numerically optimized according to the barrier loss rate, the standing wave ratio parameter and the prediction function to obtain the second path loss value.

[0100] In an embodiment of the present invention, the link quality can be detected according to the bit error rate index to obtain the link transmission quality of the heterogeneous device. In an embodiment of the present invention, the method for obtaining the link transmission quality of the heterogeneous device is not specifically limited. It should be noted that the bit error rate index can reflect the link transmission quality. Under normal working conditions, the bit error rate should be lower than 10 to the negative sixth power. By detecting the bit error rate change in real time, the antenna gain, that is, the second path loss value, can be dynamically adjusted. The transmit power compensation value can also be dynamically adjusted. When the bit error rate exceeds the threshold, the transmit power is increased or the antenna direction is adjusted.

[0101] In the embodiment of the present invention, the compensation value of the transmission power is extracted from the standing wave ratio parameter and the barrier loss rate, and the propagation attenuation constant in the second path loss value is updated according to the compensation value and the link transmission quality according to the free space loss formula to obtain the target path loss value. In the embodiment of the present invention, the method for determining the target path loss value between the first sub-device and the second sub-device according to the standing wave ratio parameter, the link transmission quality and the second path loss value is not specifically limited.

[0102] For example, see Figure 5 , obtain the antenna gain and transmission power of heterogeneous devices in the power system; extract the compensation value of the transmission power; measure the beam coupling parameter; determine the first path loss value; establish a prediction function; optimize the antenna gain; and update the propagation attenuation constant.

[0103] For example, taking the 1000-meter propagation distance in the 5.8 GHz frequency band as an example, the target path loss value of 107.7 dB after correction is reduced to 102.3 dB, and the link transmission bit error rate is improved from 10 to the negative 4th power to 10 to the negative 7th power. The free space propagation attenuation constant varies with distance, approaching 2 for short-distance transmission and increasing to about 4 for long-distance transmission. The calculated result of the corrected target path loss value is within 3 dB of the measured data.

[0104] In an embodiment of the present invention, by determining the second path loss value and determining the target path loss value between the first sub-device and the second sub-device based on the standing wave ratio parameter, the link transmission quality and the second path loss value, the influence of the inaccurate target path loss value on the accuracy of the determined abnormal traffic can be further avoided.

[0105] Figure 6It is a flowchart of another heterogeneous device communication adjustment method provided in an embodiment of the present invention. This embodiment is optimized based on the above-mentioned technical solutions. In this embodiment, optionally, the heterogeneous device communication adjustment method also includes: determining the numerical range of the channel fading index of the heterogeneous device; determining the abnormal traffic from the communication data traffic according to the target path loss value, including: determining the abnormal traffic from the communication data traffic according to the target path loss value and the numerical range. Among them, the explanations of the terms that are the same or corresponding to the above-mentioned embodiments are not repeated here.

[0106] See also Figure 6 The method of this embodiment may specifically include the following steps:

[0107] S410. Obtain antenna gain and transmission power of heterogeneous devices in the power system, and a propagation distance between a first sub-device and a second sub-device in the heterogeneous devices, and determine a target path loss value between the first sub-device and the second sub-device based on the antenna gain, transmission power, and propagation distance.

[0108] S420: Acquire the communication data flow between the first sub-device and the second sub-device.

[0109] S430: Determine a numerical range of a channel fading index of a heterogeneous device.

[0110] The channel fading index is a parameter used to describe the characteristic of the signal strength of the communication channel between the first sub-device and the second sub-device changing with the distance. The value interval is the interval range in which the value of the channel fading index may be located.

[0111] In the embodiment of the present invention, the method for determining the numerical range of the channel fading index of the heterogeneous device is not specifically limited.

[0112] S440: Determine abnormal traffic from communication data traffic according to the target path loss value and the numerical range.

[0113] In the embodiment of the present invention, there is no specific limitation on the method of determining abnormal traffic from communication data traffic based on the target path loss value and the numerical range.

[0114] S450: Determine the device node corresponding to the abnormal traffic.

[0115] S460: Determine the cache capacity of the device node, and determine the transmission adjustment path according to the cache capacity, and adjust the node path used for communication of the device node to the transmission adjustment path.

[0116] The technical solution of the embodiment of the present invention can improve the accuracy of abnormal traffic by determining abnormal traffic from communication data traffic based on the target path loss value and the numerical range.

[0117] An optional technical solution for determining a numerical range of a channel fading index of a heterogeneous device includes: determining channel fading data corresponding to the heterogeneous device under multiple weather conditions; and determining a numerical range of the channel fading index of the heterogeneous device based on the channel fading data corresponding to the multiple weather conditions.

[0118] The channel fading data is data associated with channel fading, and can also be understood as data that can be used to perform relevant calculations of channel fading; the channel fading data may include, for example, at least one of a refractive index parameter and a signal transmission loss value, and the like.

[0119] In the embodiment of the present invention, for the deployment environment of the heterogeneous device, the surrounding environment data of the deployment environment can be collected according to at least one of the temperature sensor, the air pressure sensor, the humidity sensor, etc., and the atmospheric refractive index calculation formula is used according to the surrounding environment data to convert the refractive index parameter and the signal transmission loss value, and the refractive index parameter and the signal transmission loss value are used as the channel fading data. In the embodiment of the present invention, there is no specific limitation on the method of determining the channel fading data corresponding to the heterogeneous device under multiple weather conditions. It should be noted that the refractive index parameter reflects the propagation characteristics of electromagnetic waves in the atmosphere, and is calculated by measuring basic meteorological parameters through temperature sensors, air pressure sensors, humidity sensors, etc. The refractive index decreases by about 4 units for every 10 degrees Celsius increase in temperature, increases by about 2 units for every 10% increase in relative humidity, and increases by about 3 units for every 10 hPa increase in air pressure. Under typical meteorological conditions, the refractive index value ranges from 300 to 400. When an inversion layer appears, the refractive index changes with altitude at a rate exceeding -157 / km, resulting in abnormal propagation of electromagnetic waves.

[0120] In the embodiment of the present invention, the spatial distribution characteristic parameters can also be calculated by reading the raindrop density data through the rain sensor, and the channel fading data can be determined according to the spatial distribution characteristic parameters, the refractive index parameters and the signal transmission loss value.

[0121] In the embodiment of the present invention, the wireless fading data corresponding to the wireless channels of heterogeneous devices under multiple weather conditions can also be determined by a wireless channel test instrument, and the wireless fading data can characterize the fading characteristics under different propagation environments; according to the wireless fading data, a wireless data set reflecting the fading of the wireless channel can be determined; according to the wireless data set, the channel fading caused by the multipath effect and the channel fading caused by the shadow effect are determined, and for the channel fading caused by the multipath effect, a multipath effect mathematical model is constructed by a statistical method, and for the channel fading caused by the shadow effect, a shadow effect mathematical model is constructed by a log-normal distribution method; according to the channel fading data corresponding to multiple weather conditions, the multipath effect mathematical model and the shadow effect mathematical model, the numerical range of the channel fading index of the heterogeneous device is determined. In the embodiment of the present invention, the method of determining the numerical range of the channel fading index of the heterogeneous device according to the channel fading data corresponding to multiple weather conditions is not specifically limited. It should be noted that the determination of wireless fading data can specifically be to obtain the characteristics of the impact of meteorological conditions on the channel. Weather parameters are collected through precipitation sensors, anemometers, and visibility meters. Precipitation is in millimeters per hour, and typical values ​​are 0.1 to 1 in light rain, 4 to 16 in heavy rain, and more than 16 in rainstorms. Wind speed is measured in meters per second, 1 to 5 in light breezes, and 10 to 20 in strong winds. Visibility is in kilometers, exceeding 10 in clear days and less than 1 in foggy days. Air temperature and relative humidity affect the air refractive index and absorption loss respectively. Every increase of 10 degrees Celsius in temperature leads to an increase of 0.1 decibels per kilometer in attenuation, and every increase of 10% in relative humidity increases the attenuation by 0.2 decibels per kilometer.

[0122] In an embodiment of the present invention, the signal strength data corresponding to the precipitation, wind speed, visibility, temperature and humidity, etc. corresponding to the wireless channels of heterogeneous devices under multiple weather conditions can also be collected according to the wireless channel testing instrument, and the signal strength data can be processed by a wavelet denoiser to eliminate background noise, so as to obtain the wireless fading data corresponding to the wireless channels under multiple weather conditions; the wireless fading data can be resampled according to the time interval determined by the Shannon sampling theorem, and the single-path channel fading data set can be obtained by calculating the signal attenuation ratio and the channel loss gradient according to the resampling result; the power delay spectrum corresponding to the single-path channel fading data set can be measured by a power delay spectrometer, and the arrival time and relative power of the multipath signal can be extracted from the power delay spectrum; the power delay spectrum sequence of the multipath signal that varies with time can be recorded at a fixed sampling interval, and the arrival time, relative power, power delay spectrum sequence and the single-path channel fading data set can be fused to obtain the multipath channel fading data set; The time-memory neural network processes the power delay spectrum sequence in the multipath channel fading data set, and constructs the multipath effect mathematical expression using the mean, variance, skewness and kurtosis of the multipath signal of each propagation path in the multipath channel fading data set. According to the multipath effect mathematical expression, the power superposition curve and the phase superposition curve of the multipath signal are calculated, and the multipath effect fading characteristic function is obtained according to the power superposition curve and the phase superposition curve. According to the obstacle occlusion detector, the shadow area distribution map of the deployment environment and the corresponding signal attenuation value are obtained, and the effective measurement data points are selected with the root mean square error less than the preset root mean square error threshold as the screening standard, that is, if the root mean square error is less than the root mean square error threshold, the corresponding signal attenuation value is selected, and the signal attenuation distribution of the shadow area is fitted with the log-normal distribution probability density function to obtain the shadow effect fading characteristic function; according to the shadow effect fading characteristic function and the corresponding channel fading data under multiple weather conditions, the value range of the channel fading index of the heterogeneous device is determined.It should be noted that the multipath effect is caused by the reflection of electromagnetic waves from the ground or buildings to form multiple propagation paths. The delay difference and phase difference of each path signal can be obtained through the relevant measurements of the channel analyzer. In the urban environment, the typical delay difference is 0.1 to 2 microseconds, and the phase difference is 0 to 360 degrees; the shadow effect is manifested as the additional loss caused by the signal being blocked by obstacles, and the signal strength attenuation rate in the shadow area is between 0.3 and 1 dB / m; the rate delay spectrum measurement reflects the time domain characteristics of the multipath signal, including the two dimensions of signal arrival time and relative power; in the urban environment A typical power delay spectrum shows 3 to 5 main propagation paths. The direct path signal delay is 0, and the reflected path signal delay is distributed in the range of 0.1 to 2 microseconds. The relative power is 5 to 20 decibels lower than the direct path. Continuous measurement at a fixed position can obtain the change pattern of the power delay spectrum over time. The sampling interval is 1 / 10 of the inverse of the maximum Doppler frequency shift of the signal, and the typical value is 1 to 10 milliseconds. Obstacle occlusion detection determines the boundary of the shadow area through signal strength measurement and draws a distribution diagram of occlusion loss. The multipath effect causes random changes in signal amplitude and phase. The statistical characteristics of the signal include four parameters: mean, variance, skewness and kurtosis. The mean reflects the average signal strength, which is usually 3 to 6 decibels lower than the free space propagation loss. The variance describes the intensity of signal fluctuations, with a typical value of 4 to 8 decibels in urban environments. Positive skewness indicates a high probability of deep fading, while negative skewness indicates that shallow fading is dominant. A kurtosis greater than 3 indicates a concentrated distribution of fading amplitudes, while a kurtosis less than 3 indicates a dispersed distribution. The long short-term memory neural network processes the power delay spectrum sequence through a double-layer structure of 64 neurons, and outputs a power superposition curve and a phase superposition curve. line; the shadow effect fading obeys the lognormal distribution, and the probability density function is determined by two parameters: the mean and the standard deviation; the mean reflects the average attenuation level, and the additional loss caused by obstacles in urban environments is usually between 10 and 30 decibels; the standard deviation describes the severity of the attenuation change, and the typical value is 4 to 8 decibels; the root mean square error is used to evaluate the fitting effect, and when the threshold is set to 1 decibel, the proportion of data points screened out accounts for about 85% of the total; the fitting parameters of the lognormal distribution change with the propagation environment, and the standard deviation in densely built areas is about 50% larger than that in open areas.

[0123] In an embodiment of the present invention, by determining the numerical range of the channel fading index of the heterogeneous device based on the channel fading data corresponding to multiple weather conditions, the numerical range of the channel fading index can be made suitable for different weather conditions in the environment where the heterogeneous device is located, thereby improving the accuracy of the abnormal traffic determined subsequently.

[0124] On the basis of the above scheme, an optional technical scheme is provided, which determines the numerical range of the channel fading index of the heterogeneous device according to the channel fading data corresponding to multiple weather conditions, including: obtaining the scattering angle data of the heterogeneous device obtained by antenna scanning, and determining the first fading parameter sequence according to the scattering angle data and the channel fading data corresponding to multiple weather conditions; performing a fitting operation on the first fading parameter sequence, and determining the numerical range of the channel fading index of the heterogeneous device according to the fitting result and the coherent bandwidth and reference received signal level of the heterogeneous device.

[0125] The scattering angle data refers to the angle information of the deviation from the original propagation direction caused by the scattering phenomenon when the electromagnetic wave encounters an object or medium. The first fading parameter sequence is a sequence that can characterize the channel fading situation determined by the channel fading data corresponding to multiple weather conditions. The coherence bandwidth refers to the frequency range in which the channel can be regarded as flat fading within the bandwidth of the communication between the first sub-device and the second sub-device. The reference received signal level is the standard or reference received signal strength set to ensure normal communication between the first sub-device and the second sub-device.

[0126] Exemplarily, a channel analyzer can be used to obtain the time delay difference value and phase difference value of the multipath signal component, and the time delay difference value and phase difference value of the multipath signal component are used to scan the directional antenna to obtain the scattering angle data; a first fading parameter sequence is constructed according to the scattering angle data and the channel fading data; a deep neural network is used to fit the first fading parameter sequence, and a second fading parameter sequence is constructed and a fading depth parameter is determined according to the fitting result, the coherent bandwidth and the reference received signal level; if the skewness coefficient and the kurtosis coefficient of the second fading parameter sequence exceed the preset channel fading threshold, a random forest regressor is used to divide the fading depth parameter into intervals, and the numerical interval of the channel fading index of the heterogeneous device is output. In the embodiment of the present invention, there is no specific limitation on the method of obtaining the scattering angle data of the heterogeneous device obtained by antenna scanning, and determining the first fading parameter sequence according to the scattering angle data and the channel fading data corresponding to multiple weather conditions. It should be noted that when directional antennas scan and measure scattering angle data, the arrival angle of the main reflection path is usually concentrated within the range of ±30 degrees, while the scattering path is more dispersed. The deep neural network can be a network that uses a multi-layer perceptron structure to process fading parameter sequences. Its input layer can include at least one corresponding neuron among the fitting results, environmental scattering amplitude, multipath reflection intensity, and shadow area channel fading amplitude change rate, etc. The hidden layer adopts a double-layer structure of 64 neurons, and the output layer corresponds to 32 sampling points of the probability density function. The fading depth parameter characterizes the fluctuation amplitude of the signal strength relative to the reference level, and the value range is usually between 15 and 40 decibels. The random forest regressor jointly analyzes the fading depth parameter and the channel flatness parameter, and divides the channel state into a mild fading interval, a moderate fading interval, and a deep fading interval, and the corresponding fading index values ​​are 1 to 2, 2 to 4, and 4 to 6, respectively.

[0127] Exemplarily, the environmental scattering amplitude can be calculated based on the scattering angle data; the multipath reflection intensity can be calculated based on the environmental scattering amplitude and the reference received signal level; the change rate of the channel fading amplitude in the shadow area can be determined based on the channel fading data, and a first fading parameter sequence can be constructed based on the change rate of the channel fading amplitude in the shadow area; the first fading parameter sequence is fitted by a deep neural network, the channel flatness parameter is determined based on the coherent bandwidth, the fading depth parameter is calculated based on the reference received signal level, and the fitting result, the environmental scattering amplitude, the multipath reflection intensity and the change rate of the channel fading amplitude in the shadow area are input into the deep neural network to construct a second fading parameter sequence, and a channel fading probability density curve is generated based on the second fading parameter sequence; the distribution characteristics of the second fading parameter sequence are calculated based on the skewness coefficient and the kurtosis coefficient of the channel fading probability density curve, and the fading depth parameter and the channel flatness parameter are divided into intervals based on the distribution characteristics using a random forest regressor, the fading degree level is determined by comparing it with a preset channel fading threshold parameter table, and the numerical interval of the channel fading index of the heterogeneous device is output. It should be noted that the shape characteristics of the channel fading probability density curve are described by the skewness coefficient and the kurtosis coefficient. The skewness coefficient reflects the asymmetry of the distribution. Positive skewness indicates that the probability of deep fading is higher, and negative skewness indicates that shallow fading is dominant. The kurtosis coefficient reflects the concentration of the distribution. A value greater than 3 indicates that the fading amplitude distribution is more concentrated. The preset channel fading threshold parameter table is determined based on measured statistical data. Mild fading corresponds to a fading depth less than 20 decibels and a coherent bandwidth greater than 5 MHz. Deep fading corresponds to a fading depth greater than 35 decibels or a coherent bandwidth less than 1 MHz.

[0128] In an embodiment of the present invention, a probability distribution curve of the first fading parameter sequence can be fitted, and the severity of the channel fading can be determined by the curve shape characteristics characterized by the fitting result, the coherent bandwidth of the heterogeneous device, and the reference received signal level. According to the severity, the numerical range of the channel fading index of the heterogeneous device is determined. In an embodiment of the present invention, the first fading parameter sequence is fitted, and the numerical range of the channel fading index of the heterogeneous device is determined according to the fitting result, the coherent bandwidth of the heterogeneous device, and the reference received signal level. There is no specific limitation. It should be noted that the coherent bandwidth reflects the frequency selectivity characteristics of the channel, and is defined by the 3 dB bandwidth of the frequency correlation function. The typical value is 0.5 to 5 MHz in an urban environment and 2 to 20 MHz in a suburban environment.

[0129] In an embodiment of the present invention, a fitting operation is performed according to the first fading parameter sequence, and the numerical range of the channel fading index of the heterogeneous device is determined according to the fitting result and the coherent bandwidth and reference received signal level of the heterogeneous device, which can improve the accuracy of the abnormal traffic determined subsequently.

[0130] In order to better understand the technical solution of the above embodiment of the present invention, an optional example is provided here. Figure 7, obtain the antenna gain and transmission power of the heterogeneous devices in the power system, and the propagation distance between the first sub-device and the second sub-device in the heterogeneous devices, and determine the target path loss value between the first sub-device and the second sub-device according to the antenna gain, transmission power and propagation distance; determine the channel fading data corresponding to the heterogeneous devices under multiple weather conditions according to the deployment environment of the heterogeneous devices, and construct a multipath effect mathematical model and a shadow effect mathematical model according to the channel fading data, the multipath effect mathematical model and the shadow effect mathematical model according to the channel fading data corresponding to the multiple weather conditions, the multipath effect mathematical model and the shadow effect mathematical model, and determine the numerical range of the channel fading index of the heterogeneous devices; determine the theoretical signal transmission strength between the first sub-device and the second sub-device according to the target path loss value and the signal frequency parameter, determine the potential interference source information of the heterogeneous devices within a preset range, and correct the theoretical signal transmission strength according to the potential interference source information to obtain the actual signal transmission strength between the first sub-device and the second sub-device; according to the link bandwidth value and the data packet size The invention discloses a method for detecting a small amount of traffic between a first sub-device and a second sub-device, wherein the traffic detection tool is used to collect the communication data traffic between the first sub-device and the second sub-device in real time, analyze the communication data traffic, obtain the data traffic proportion corresponding to at least one communication protocol, determine the abnormal traffic from the communication data traffic according to the numerical range, the data traffic proportion corresponding to at least one communication protocol and the actual signal transmission strength, and determine the device node corresponding to the abnormal traffic; evaluate the congestion level of the device node according to the cache capacity, and when the congestion level exceeds the preset congestion level threshold, calculate the transmission adjustment path according to the preset number of backup paths and the routing table update cycle, so as to guide the device node to the transmission adjustment path, and complete the load balancing of the abnormal traffic; after completing the load balancing of the abnormal traffic, continuously detect the change trend of the communication data traffic between the first sub-device and the second sub-device, draw a curve chart of the change trend of the communication data traffic according to the obtained change trend, and dynamically adjust the node path of the device node for communication according to the curve chart, so as to keep the network in a preset stable state. The above technical scheme takes into account the problem that the signal transmission of heterogeneous devices in a complex propagation environment is unstable due to multipath effects, shadow effects and potential interference sources, which easily causes network congestion. A solution based on channel fading correction and load balancing is proposed. By determining the target path loss value, constructing multipath and shadow effect models, and combining interference correction, the actual signal transmission strength is obtained. According to the numerical range and the actual signal transmission strength, the abnormal traffic and device nodes that cause congestion are identified. The impact of channel fading on network performance is simulated and analyzed to provide data support for identifying abnormal traffic. The load balancing mechanism is triggered according to the degree of node congestion, the transmission adjustment path is calculated and the abnormal traffic is diverted to the transmission adjustment path, and the path is dynamically adjusted by continuously detecting the traffic change trend to maintain network stability, effectively improving the stability and reliability of the heterogeneous device communication network in a complex environment, and ensuring the safe and efficient operation of the power system.

[0131] Figure 8 This is a structural block diagram of a heterogeneous device communication adjustment device provided in an embodiment of the present invention, and the device is used to execute the heterogeneous device communication adjustment method provided in any of the above embodiments. The device and the heterogeneous device communication adjustment method of the above embodiments belong to the same inventive concept. For details not described in detail in the embodiment of the heterogeneous device communication adjustment device, please refer to the embodiment of the above heterogeneous device communication adjustment method. Figure 8 The device may specifically include: a target path loss value determination module 510, a device node determination module 520 and a transmission adjustment path adjustment module 530.

[0132] Among them, the target path loss value determination module 510 is used to obtain the antenna gain and transmission power of the heterogeneous devices in the power system, as well as the propagation distance between the first sub-device and the second sub-device in the heterogeneous devices, and determine the target path loss value between the first sub-device and the second sub-device based on the antenna gain, transmission power and propagation distance; the device node determination module 520 is used to obtain the communication data flow between the first sub-device and the second sub-device, determine the abnormal flow from the communication data flow according to the target path loss value, and determine the device node corresponding to the abnormal flow; the transmission adjustment path adjustment module 530 is used to determine the cache capacity of the device node, and determine the transmission adjustment path based on the cache capacity, and adjust the node path of the device node used for communication to the transmission adjustment path.

[0133] Optionally, the device node determination module 520 includes: an actual signal transmission strength determination submodule, used to obtain the signal frequency parameters of the heterogeneous device, and determine the actual signal transmission strength between the first sub-device and the second sub-device based on the target path loss value and the signal frequency parameters; a first abnormal traffic determination submodule, used to determine abnormal traffic from the communication data traffic based on the actual signal transmission strength.

[0134] Optionally, based on the above-mentioned device, the actual signal transmission strength determination submodule includes: a theoretical signal transmission strength determination unit, which is used to determine the theoretical signal transmission strength between the first sub-device and the second sub-device based on the target path loss value and the signal frequency parameter; an actual signal transmission strength acquisition unit, which is used to determine the potential interference source information of heterogeneous devices within a preset range, and correct the theoretical signal transmission strength according to the potential interference source information to obtain the actual signal transmission strength between the first sub-device and the second sub-device.

[0135] Optionally, the target path loss value determination module 510 includes: a spatial attenuation compensation value determination submodule, used to determine the spatial attenuation compensation value between the first subdevice and the second subdevice based on the antenna gain and the transmission power; a first path loss value determination submodule, used to determine the first path loss value based on the antenna gain and the propagation distance; a target path loss value determination submodule, used to obtain a standing wave ratio parameter, and determine the target path loss value between the first subdevice and the second subdevice based on the spatial attenuation compensation value, the first path loss value and the standing wave ratio parameter.

[0136] Optionally, based on the above-mentioned device, a target path loss value determination submodule includes: a second path loss value determination unit, used to determine the second path loss value between the first sub-device and the second sub-device based on the standing wave ratio parameter, the spatial attenuation compensation value and the first path loss value; a target path loss value determination unit, used to obtain the link transmission quality of the heterogeneous device, and determine the target path loss value between the first sub-device and the second sub-device based on the standing wave ratio parameter, the link transmission quality and the second path loss value.

[0137] Optionally, the device also includes: a numerical interval determination module, used to determine the numerical interval of the channel fading index of the heterogeneous device; the device node determination module 520, including: a second abnormal traffic determination submodule, used to determine abnormal traffic from the communication data traffic based on the target path loss value and the numerical interval.

[0138] Optionally, based on the above-mentioned device, the numerical interval determination module includes: a channel fading data determination submodule, used to determine the channel fading data corresponding to the heterogeneous devices under multiple weather conditions; a numerical interval determination submodule, used to determine the numerical interval of the channel fading index of the heterogeneous devices based on the channel fading data corresponding to the multiple weather conditions.

[0139] Optionally, based on the above-mentioned device, a numerical interval determination submodule includes: a first fading parameter sequence determination subunit, used to obtain scattering angle data of the heterogeneous device obtained by antenna scanning, and determine the first fading parameter sequence according to the scattering angle data and the channel fading data corresponding to multiple weather conditions; a numerical interval determination subunit, used to perform a fitting operation on the first fading parameter sequence, and determine the numerical interval of the channel fading index of the heterogeneous device according to the fitting result and the coherent bandwidth and reference received signal level of the heterogeneous device.

[0140] Optionally, the device node determination module 520 includes: a data traffic proportion obtaining sub-module, used to analyze the communication data traffic to obtain the data traffic proportion corresponding to at least one communication protocol; a third abnormal traffic determination sub-module, used to determine abnormal traffic from the communication data traffic according to the data traffic proportion corresponding to at least one communication protocol and the target path loss value.

[0141] Optionally, the transmission adjustment path adjustment module 530 includes: a congestion level assessment submodule, used to assess the congestion level of the device node according to the cache capacity; and a transmission adjustment path determination submodule, used to determine the transmission adjustment path when the congestion level exceeds a preset level threshold.

[0142] The heterogeneous device communication adjustment device provided in the embodiment of the present invention obtains the antenna gain and transmission power of the heterogeneous device in the power system and the propagation distance between the first sub-device and the second sub-device in the heterogeneous device through a target path loss value determination module, and determines the target path loss value between the first sub-device and the second sub-device according to the antenna gain, the transmission power and the propagation distance, so as to determine the loss of the heterogeneous device communication; obtains the communication data flow between the first sub-device and the second sub-device through a device node determination module, determines the abnormal flow from the communication data flow according to the target path loss value, and determines the device node corresponding to the abnormal flow to determine the device node with the abnormal flow; determines the cache capacity of the device node through a transmission adjustment path adjustment module, and determines the transmission adjustment path according to the cache capacity, and adjusts the node path of the device node used for communication to the transmission adjustment path, so as to adjust the node path that affects the effectiveness of the heterogeneous device communication. The above-mentioned device can determine the device node corresponding to the abnormal traffic that affects the effectiveness of heterogeneous device communication through the target path loss value, and adjust the node path used by the device node for communication to avoid the impact of abnormal communication between device nodes on heterogeneous device communication, thereby improving the effectiveness of heterogeneous device communication.

[0143] The heterogeneous device communication adjustment device provided in the embodiment of the present invention can execute the heterogeneous device communication adjustment method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0144] It is worth noting that in the above-mentioned embodiment of the heterogeneous device communication adjustment device, the various units and modules included are only divided according to functional logic, but are not limited to the above-mentioned division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present invention.

[0145] Fig. 9A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0146] like Fig. 9 As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0147] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0148] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as a heterogeneous device communication adjustment method.

[0149] In some embodiments, the heterogeneous device communication adjustment method may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the heterogeneous device communication adjustment method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform the heterogeneous device communication adjustment method in any other appropriate manner (e.g., by means of firmware).

[0150] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0151] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine as a stand-alone software package and partially on a remote machine, or entirely on a remote machine or server.

[0152] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, device, or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0153] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0154] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0155] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0156] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0157] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for adjusting communication between heterogeneous devices, characterized in that: include: Obtaining antenna gain and transmission power of a heterogeneous device in the power system, and a propagation distance between a first sub-device and a second sub-device in the heterogeneous device, and determining a target path loss value between the first sub-device and the second sub-device according to the antenna gain, the transmission power, and the propagation distance; Acquire the communication data flow between the first sub-device and the second sub-device, determine abnormal flow from the communication data flow according to the target path loss value, and determine the device node corresponding to the abnormal flow; The cache capacity of the device node is determined, and a transmission adjustment path is determined according to the cache capacity, and a node path used for communication of the device node is adjusted to the transmission adjustment path.

2. The method according to claim 1, characterized in that The determining abnormal traffic from the communication data traffic according to the target path loss value includes: Acquire a signal frequency parameter of the heterogeneous device, and determine an actual signal transmission strength between the first sub-device and the second sub-device according to the target path loss value and the signal frequency parameter; According to the actual signal transmission strength, abnormal traffic is determined from the communication data traffic.

3. The method according to claim 2, characterized in that The determining, according to the target path loss value and the signal frequency parameter, an actual signal transmission strength between the first sub-device and the second sub-device includes: Determining a theoretical signal transmission strength between the first sub-device and the second sub-device according to the target path loss value and the signal frequency parameter; The potential interference source information of the heterogeneous device within a preset range is determined, and the theoretical signal transmission strength is corrected according to the potential interference source information to obtain the actual signal transmission strength between the first sub-device and the second sub-device.

4. The method according to claim 1, characterized in that: The determining, according to the antenna gain, the transmit power, and the propagation distance, a target path loss value between the first sub-device and the second sub-device includes: Determining a spatial attenuation compensation value between the first sub-device and the second sub-device according to the antenna gain and the transmit power; Determining a first path loss value according to the antenna gain and the propagation distance; A standing wave ratio parameter is obtained, and a target path loss value between the first sub-device and the second sub-device is determined according to the spatial attenuation compensation value, the first path loss value, and the standing wave ratio parameter.

5. The method according to claim 4, characterized in that The determining, according to the spatial attenuation compensation value, the first path loss value, and the standing wave ratio parameter, a target path loss value between the first sub-device and the second sub-device includes: Determine a second path loss value between the first sub-device and the second sub-device according to the standing wave ratio parameter, the spatial attenuation compensation value and the first path loss value; The link transmission quality of the heterogeneous device is obtained, and a target path loss value between the first sub-device and the second sub-device is determined according to the standing wave ratio parameter, the link transmission quality and the second path loss value.

6. The method according to claim 1, characterized in that Also includes: Determining a numerical range of a channel fading index of the heterogeneous device; The determining abnormal traffic from the communication data traffic according to the target path loss value includes: According to the target path loss value and the numerical range, abnormal traffic is determined from the communication data traffic.

7. The method according to claim 6, characterized in that The determining of the numerical range of the channel fading index of the heterogeneous device includes: Determining channel fading data corresponding to the heterogeneous devices respectively under multiple weather conditions; According to the channel fading data respectively corresponding to the multiple weather conditions, a numerical range of the channel fading index of the heterogeneous device is determined.

8. The method according to claim 7, characterized in that The determining, according to the channel fading data respectively corresponding to the plurality of weather conditions, a numerical range of the channel fading index of the heterogeneous device comprises: Acquire scattering angle data of the heterogeneous device obtained by antenna scanning, and determine a first fading parameter sequence according to the scattering angle data and the channel fading data respectively corresponding to the multiple weather conditions; A fitting operation is performed on the first fading parameter sequence, and a numerical range of a channel fading index of the heterogeneous device is determined according to the fitting result and the coherent bandwidth and the reference received signal level of the heterogeneous device.

9. The method according to claim 1, characterized in that: The determining abnormal traffic from the communication data traffic according to the target path loss value includes: Analyze the communication data flow to obtain the data flow ratio corresponding to at least one communication protocol; According to the data flow ratio respectively corresponding to the at least one communication protocol and the target path loss value, abnormal flow is determined from the communication data flow.

10. The method according to claim 1, characterized in that The determining of the transmission adjustment path according to the cache capacity includes: According to the cache capacity, evaluating the congestion level of the device node; When the congestion level exceeds a preset level threshold, a transmission adjustment path is determined.

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