Intelligent building weak current equipment multi-protocol compatible method and system and storage medium

Abstract

The invention relates to the technical field of network resource management, and discloses an intelligent building weak current equipment multi-protocol compatible method and system, and a storage medium. The method comprises the steps of collecting multi-protocol network data streams, extracting data packet lengths and arrival interval time as classification features, dividing network data packets into three data packet groups of short and small high frequency, medium stability and large flow, and forming a real-time response network sequence through a priority queue scheduling mechanism and preferentially transmitting the short and small high frequency groups, the method comprises the steps of receiving a real-time response sequence, calculating residual bandwidth to adjust a network buffer area, packaging and splitting a large-flow data packet group to generate transmission sub-blocks, merging the real-time response sequence and the transmission sub-blocks through a merging rule, dividing the merged real-time response sequence and the transmission sub-blocks into a plurality of data stream segments, and distributing a transmission path for each data stream segment. And monitoring bandwidth occupation and transmission delay of each transmission path, and dynamically adjusting path distribution of the data stream segments. According to the invention, the utilization efficiency of network resources and the real-time performance of data transmission in a multi-protocol environment are improved.

Description

Technical Field

[0001] This application relates to the field of network resource management technology, and in particular to a method, system and storage medium for multi-protocol compatibility of intelligent building low-voltage equipment. Background Technology

[0002] Intelligent building systems typically consist of multiple network devices that interconnect and collaborate via various protocols. However, in practical applications, protocol compatibility issues in intelligent buildings often lead to low communication efficiency, resource waste, and poor inter-device interaction. Common devices in intelligent buildings include security monitoring systems, environmental control systems, lighting systems, sensors, and control panels. These devices often employ different communication protocols, such as Modbus, BACnet, and KNX. Data exchange between these devices and systems typically encounters several problems, such as poor interoperability between different protocols, excessive data transmission latency, and insufficient network bandwidth.

[0003] In multi-protocol network environments, information exchange between devices is often limited by issues such as protocol incompatibility, network congestion, and insufficient bandwidth utilization. This is especially true in smart buildings where the number and types of devices are large, leading to significant fluctuations in network load and latency. Furthermore, traditional network scheduling and bandwidth allocation methods typically rely on fixed thresholds to handle network traffic. This is ill-suited to diverse needs under unstable network load and latency conditions, potentially resulting in unnecessary data fragmentation or excessive transmission delays.

[0004] Therefore, existing technologies urgently need an optimized, dynamic multi-protocol compatibility method to improve the communication efficiency of low-voltage equipment in intelligent buildings, ensure the reasonable scheduling of various data packets, reduce bandwidth consumption, improve network resource utilization, and thus enhance the collaborative working efficiency between devices. Faced with complex network environments characterized by high load, bandwidth fluctuations, and latency variations, this application proposes a highly adaptable, flexible, and resource-optimized multi-protocol compatibility method for low-voltage equipment in intelligent buildings. Summary of the Invention

[0005] To address the aforementioned technical issues, this application provides a method, system, and storage medium for multi-protocol compatibility of intelligent building low-voltage equipment, which improves the utilization efficiency of network resources and the real-time performance of data transmission in a multi-protocol environment.

[0006] In a first aspect, this application provides a method for multi-protocol compatibility of low-voltage electrical equipment in intelligent buildings, the method comprising:

[0007] Step S1: Obtain the multi-protocol network data stream of the low-voltage equipment in the intelligent building, and extract the length value and arrival interval of each network data packet from the multi-protocol network data stream to form network classification features;

[0008] Step S2: Based on the network classification characteristics, classify the network data packets into short, high-frequency network data packet groups, medium-stability network data packet groups, and high-volume network data packet groups;

[0009] Step S3: Through the priority queue scheduling mechanism, prioritize the transmission of data packets in the short high-frequency network data packet group to form a real-time response network sequence. Based on the transmission status of the real-time response network sequence, calculate the remaining bandwidth for transmitting the medium stable network data packet group and the high-volume network data packet group.

[0010] Step S4: Based on the remaining bandwidth, adjust the network buffer occupancy rate and perform batch packaging processing on the large-volume network data packet group to generate an optimized transmission block. When the length of the optimized transmission block exceeds a preset value, split the optimized transmission block into multiple transmission sub-blocks. Based on the sequence merging rule, merge the real-time response network sequence with the transmission sub-blocks to form a merged data stream, and divide the merged data stream into multiple data stream segments.

[0011] Step S5: Assign a network transmission path to each data stream segment, monitor the bandwidth usage and transmission delay of each transmission path in real time, and dynamically adjust the path allocation and network buffer resources of the data stream segments based on the monitoring results to complete the data transmission.

[0012] In conjunction with the first aspect, in the first implementation of the first aspect of this application, the formation of network classification features in step S1 includes:

[0013] Calculate the mean of the network data packet length and the standard deviation of the data packet arrival interval, and use the mean and the standard deviation as network classification features.

[0014] In conjunction with the first aspect, in the second implementation of the first aspect of this application, step S2 includes:

[0015] The network data packets are grouped using a clustering algorithm to obtain preliminary grouping results;

[0016] Based on the protocol type and traffic distribution characteristics of each group in the preliminary grouping results, a classification model is used to identify and confirm short, high-frequency network data packet groups, medium-stability network data packet groups, and high-volume network data packet groups.

[0017] In conjunction with the first aspect, in the third implementation of the first aspect of this application, step S3, forming a real-time response network sequence, includes:

[0018] For short, high-frequency data packet groups, the data packets within the group are sorted based on their arrival time, priority label, and urgency level to generate a priority queue scheduling mechanism, and the transmission order of the data packets is adjusted to generate an initial response network sequence.

[0019] Based on the initial response network sequence, the timing characteristics of the short, high-frequency data packet group are extracted, and the transmission stability of the data packet is determined based on the timing characteristics to identify a stable transmission sequence.

[0020] From the stable transmission sequence, the transmission interval distribution of short high-frequency data packets is obtained, and the transmission interval distribution is compared with a preset threshold. If the threshold condition is met, the stable transmission sequence is determined to be a real-time response network sequence.

[0021] If the threshold condition is not met, the scheduling strategy of the priority queue scheduling mechanism is readjusted based on the stable transmission sequence until the threshold condition is met and it is determined as a real-time response network sequence.

[0022] In conjunction with the first aspect, in the fourth implementation of the first aspect of this application, step S4, adjusting the network buffer occupancy rate based on the remaining bandwidth resources, includes:

[0023] Based on the real-time response network sequence, the bandwidth usage of medium-stable data packet groups and high-volume data packet groups is analyzed, and the remaining bandwidth resources are calculated using a weighted average method to determine the bandwidth allocation set.

[0024] Real-time network buffer occupancy data is extracted using bandwidth allocation sets;

[0025] If the real-time occupied data exceeds a preset threshold, the sliding window method is used to adjust the allocation ratio of the dynamic adjustment buffer among each data packet group to obtain an optimized buffer sequence.

[0026] The real-time occupancy rate is obtained by calculating the ratio of the total number of cached data packets in the buffer to the total capacity of the buffer based on the optimized buffer sequence. The network buffer occupancy rate is then obtained by performing a sliding average on the real-time occupancy rate over a continuous time window.

[0027] In conjunction with the first aspect, in the fifth implementation of the first aspect of this application, the optimized transport block obtained in step S4 includes:

[0028] Determine whether the network buffer occupancy rate is lower than a preset threshold. If yes, maintain the existing scheduling; otherwise, determine that the network buffer is in a high-occupancy state and adjust the resource allocation ratio through a dynamic allocation algorithm to generate a ratio adjustment set.

[0029] Based on the proportional adjustment set, a batch packaging method is used to integrate data packets for large-volume data packet groups to obtain optimized transmission blocks.

[0030] In conjunction with the first aspect, in the sixth implementation of the first aspect of this application, step S4, merging the real-time response network sequence with the transport sub-block to form a merged data stream, includes:

[0031] The sequence merging rules are set according to the priority of data packets, the timing alignment is performed based on the arrival timestamp of data packets, and the transmission of the real-time response network sequence is prioritized when bandwidth contention occurs in the same time period. The sub-block network sequences are then queued and adjusted to obtain the merged data packet sequence.

[0032] The merged data packet sequence is divided into multiple data stream segments, each of which has a corresponding bandwidth usage value and transmission path identifier.

[0033] In conjunction with the first aspect, in the seventh implementation of the first aspect of this application, step S5 includes:

[0034] The data stream fragments are allocated to multiple independent network paths using a multipath transmission protocol to obtain a multipath allocation set;

[0035] Based on the multi-path allocation set, the transmission delay of each network path is continuously monitored using the sliding window method, and the network delay value is extracted to form a delay distribution sequence.

[0036] If the network latency value of a path in the delay distribution sequence exceeds a preset threshold, the dynamic routing adjustment algorithm is invoked to redistribute the data stream segments of the network path to form an optimized path set.

[0037] Based on the optimized path set, a weighted average method is used to reallocate network buffer resources, and the updated buffer optimization sequence is output.

[0038] Secondly, this application provides a multi-protocol compatible system for intelligent building low-voltage electrical equipment, the system comprising:

[0039] The acquisition module is used to acquire the multi-protocol network data stream of low-voltage equipment in intelligent buildings, extract the length value and arrival interval of each network data packet from the multi-protocol network data stream, and form network classification features.

[0040] The first segmentation module is used to classify the network data packets into short, high-frequency network data packet groups, medium-stability network data packet groups, and high-volume network data packet groups based on the network classification characteristics.

[0041] The calculation module is used to prioritize the transmission of data packets in the short, high-frequency network data packet group through a priority queue scheduling mechanism to form a real-time response network sequence. Based on the transmission status of the real-time response network sequence, it calculates the remaining bandwidth for transmitting the medium-stable network data packet group and the high-volume network data packet group.

[0042] The second partitioning module is used to adjust the network buffer occupancy rate based on the remaining bandwidth, and to perform batch packaging processing on the large-volume network data packet group to generate an optimized transmission block. When the length of the optimized transmission block exceeds a preset value, the optimized transmission block is split into multiple transmission sub-blocks. Based on the sequence merging rule, the real-time response network sequence is merged with the transmission sub-blocks to form a merged data stream, and the merged data stream is divided into multiple data stream segments.

[0043] The adjustment module is used to allocate network transmission paths for each data stream segment, monitor the bandwidth usage and transmission latency of each transmission path in real time, and dynamically adjust the path allocation and network buffer resources of the data stream segments based on the monitoring results to complete data transmission.

[0044] A third aspect of this application provides a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the aforementioned method for multi-protocol compatibility of intelligent building low-voltage electrical equipment.

[0045] Compared with the prior art, the beneficial effects of the present invention are at least as follows:

[0046] This application provides a method and system for multi-protocol compatibility of low-voltage electrical equipment in intelligent buildings, aiming to improve the efficiency and reliability of data transmission in a multi-protocol network environment. By classifying network data streams from low-voltage electrical equipment into short, high-frequency, medium-stability, and high-volume data packet groups, a priority queue scheduling mechanism is adopted to ensure that applications with high real-time requirements are transmitted first, reducing latency and packet loss. Furthermore, based on real-time monitoring of bandwidth usage and latency data, a dynamic routing adjustment algorithm is used to optimize the transmission path, avoiding the impact of network congestion and high-latency paths on the data stream. In addition, dynamic adjustment of network buffer resources based on remaining bandwidth enables reasonable resource allocation during high-volume periods, preventing data loss and latency caused by buffer overload. High-volume data packets are optimized through batch packaging, reducing the scheduling overhead of single-packet transmission, and further improving transmission efficiency by splitting and optimizing transmission blocks. Through intelligent classification and traffic scheduling, the compatibility and traffic allocation between different protocols are optimized, ensuring stable and efficient operation in a multi-protocol network environment. Attached Figure Description

[0047] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0048] Figure 1 This is a schematic diagram of one embodiment of the multi-protocol compatibility method for intelligent building low-voltage electrical equipment in this application.

[0049] Figure 2 This is a diagram illustrating bandwidth allocation and usage in the embodiments of this application;

[0050] Figure 3 This is a schematic diagram illustrating network path delay and dynamic routing adjustment in an embodiment of this application;

[0051] Figure 4 This is a schematic diagram of one embodiment of a multi-protocol compatible system for intelligent building low-voltage electrical equipment in this application. Detailed Implementation

[0052] This application provides a method, apparatus, device, and medium for multi-protocol compatibility of intelligent building low-voltage electrical equipment. The terms "first," "second," "third," "fourth," etc. (if present) in the specification, claims, and accompanying drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments described herein can be implemented in a sequence other than that illustrated or described herein. Furthermore, the terms "comprising" or "having" and any variations thereof are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or device that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or devices.

[0053] For ease of understanding, the specific process of the embodiments of this application is described below. Please refer to [link / reference]. Figure 1 One embodiment of the multi-protocol compatibility method for intelligent building low-voltage electrical equipment in this application includes:

[0054] Step S1: Obtain the multi-protocol network data stream of the low-voltage equipment in the intelligent building, extract the length value and arrival interval of each network data packet from the multi-protocol network data stream, and form network classification features. The formation of network classification features in step S1 includes: calculating the mean of the network data packet length value and the standard deviation of the data packet arrival interval, and using the mean and standard deviation as network classification features.

[0055] Specifically, to achieve unified management of multi-protocol network data, this step first involves data acquisition and feature extraction. Low-voltage devices include, but are not limited to, network cameras, access controllers, and environmental sensors, whose communication protocols cover various types such as TCP, UDP, and ICMP. The data acquisition module captures the network data streams generated by these devices in real time. This module employs high-performance packet processing technology well-known to those skilled in the art to ensure data integrity under high concurrency conditions. Subsequently, the captured data streams are parsed to obtain the length value and arrival timestamp of each network data packet. Based on the timestamps of consecutive data packets, the arrival interval time of adjacent data packets is calculated, forming an arrival interval time series. Finally, the mean of all data packet length values ​​is calculated, and the standard deviation of the arrival interval time series is also calculated. The length mean is used to characterize the typical load size of the data stream, while the standard deviation of the interval time is used to characterize the stability and burstiness of the data stream over time. For example, video streams generated by surveillance cameras typically exhibit a large length mean and a small interval standard deviation, while sensor alarm information typically exhibits a small length mean and a large interval standard deviation. The resulting network classification features provide a reliable numerical basis for subsequent data packet classification.

[0056] Step S2: Based on network classification characteristics, classify network data packets into short, high-frequency network data packet groups, medium-stable network data packet groups, and high-volume network data packet groups. Step S2 further includes: using a clustering algorithm to group network data packets to obtain preliminary grouping results; and using a classification model to identify and confirm the short, high-frequency network data packet groups, medium-stable network data packet groups, and high-volume network data packet groups based on the protocol type and traffic distribution characteristics of each group in the preliminary grouping results.

[0057] Specifically, an initial data packet feature set is constructed based on the extracted network classification features. To reduce the interference of redundant features on the calculation, principal component analysis is used to reduce the dimensionality of the initial feature set, retaining the feature dimensions that can explain the main differences, thus forming a dimensionality-reduced feature set. The dimensionality-reduced feature set is then input into a clustering algorithm for grouping. Clustering algorithms such as K-means or hierarchical clustering are used to automatically aggregate the data packets into three categories based on their length and arrival interval characteristics: short and high-frequency network data packet groups, medium-stable network data packet groups, and high-volume network data packet groups. Short and high-frequency network data packet groups are typically characterized by small data packet size, short arrival intervals, and high frequency, suitable for business scenarios with high real-time requirements; medium-stable network data packet groups are characterized by data packet length and arrival intervals in the middle range, suitable for periodic or stable services; and high-volume network data packet groups are characterized by large data packets and long intervals, typically corresponding to high-bandwidth consumption business scenarios. Based on the initial grouping, the protocol type composition and traffic distribution pattern of each initial group are extracted as new classification features. For example, some initial clusters may contain a large number of UDP heartbeat packets, exhibiting a pattern of "small packets, high frequency, and large interval fluctuations"; while other clusters may mainly contain TCP data, exhibiting a pattern of "large packets and continuous traffic". These enhanced features are input into a classification model for training and discrimination. The classification model includes, but is not limited to, random forest models. This process verifies, corrects, and refines the initial clustering results, ultimately assigning an accurate cluster label to each data packet. This two-stage process effectively overcomes the limitations of single classification methods and significantly improves the robustness and accuracy of the clustering results.

[0058] Step S3: Through the priority queue scheduling mechanism, data packets in the short and high-frequency network data packet group are prioritized for transmission to form a real-time response network sequence. Based on the transmission status of the real-time response network sequence, the remaining bandwidth for transmitting medium-stable network data packet groups and high-volume network data packet groups is calculated.

[0059] The step S3, forming a real-time response network sequence, includes: for short, high-frequency data packet groups, sorting the data packets within the group based on their arrival time, priority label, and urgency, generating a priority queue scheduling mechanism, and adjusting the transmission order of the data packets to generate an initial response network sequence; based on the initial response network sequence, extracting the temporal characteristics of the short, high-frequency data packet groups, judging the transmission stability of the data packets based on the temporal characteristics, and determining a stable transmission sequence; from the stable transmission sequence, obtaining the transmission interval distribution of the short, high-frequency data packet groups, comparing the transmission interval distribution with a preset threshold, and if the threshold condition is met, determining the stable transmission sequence as a real-time response network sequence; if the threshold condition is not met, readjusting the scheduling strategy of the priority queue scheduling mechanism based on the stable transmission sequence until the threshold condition is met and it is determined as a real-time response network sequence.

[0060] Specifically, short, high-frequency data packet groups typically correspond to device heartbeat information, status reports, or alarm signals. These data packets have extremely high real-time requirements. To ensure their transmission priority and stability, this step employs a closed-loop feedback mechanism to form a real-time response network sequence. First, based on the arrival time, preset priority, and urgency of the data packets, the data packets within the short, high-frequency group are dynamically sorted to form a priority queue. This queue ensures that critical data is transmitted first, thereby generating an initial response network sequence. Subsequently, the transmission timing characteristics of this initial sequence are continuously monitored, such as the jitter of the data packet intervals. If the interval distribution is stable and meets the preset threshold requirements, the sequence is directly recognized as a qualified real-time response network sequence. If monitoring detects excessive timing fluctuations that do not meet stability requirements, the system automatically adjusts the priority queue scheduling strategy, for example, by changing priority weights, adjusting the scheduling cycle, and regenerating and evaluating the sequence until its transmission stability meets the standards. This closed-loop process ensures low latency and high reliability of the real-time response network sequence. After the real-time response network sequence is formed and transmitted, the system enters the bandwidth resource calculation stage. A total bandwidth capacity is preset, and a fixed bandwidth quota is allocated to short, high-frequency data packet groups to ensure their absolute priority in service quality. The remaining bandwidth is calculated by deducting the allocated quota for short, high-frequency data packet groups from the total bandwidth. Specifically, assuming the total outbound bandwidth of the intelligent building network is 800Mbps, and to ensure real-time performance, the system statically allocates 150Mbps of bandwidth to short, high-frequency data packet groups, then the formula for calculating the remaining bandwidth is: Remaining bandwidth = Total bandwidth - Short, high-frequency group allocated bandwidth, i.e., 800Mbps - 150Mbps = 650Mbps. This 650Mbps of remaining bandwidth is the dynamic resource pool available for contention between medium-stability data packet groups and high-volume data packet groups. Through this mechanism, priority scheduling not only ensures low-latency transmission of critical data but also provides a clear real-time basis for bandwidth allocation for other types of data.

[0061] Step S4: Based on the remaining bandwidth, adjust the network buffer occupancy rate and perform batch packaging of large-volume network data packets to generate optimized transport blocks. When the length of the optimized transport block exceeds the preset value, split the optimized transport block into multiple transport sub-blocks. Based on the sequence merging rules, merge the real-time response network sequence with the transport sub-blocks to form a merged data stream, and divide the merged data stream into multiple data stream segments.

[0062] Step S4, adjusting the network buffer occupancy rate based on remaining bandwidth resources, includes: analyzing the bandwidth occupancy of moderately stable data packet groups and high-volume data packet groups based on the real-time response network sequence; calculating the remaining bandwidth resources using a weighted average method to determine the bandwidth allocation set; extracting real-time occupancy data of the network buffer using the bandwidth allocation set; if the real-time occupancy data exceeds a preset threshold, adjusting the allocation ratio of the dynamic buffer among each data packet group using a sliding window method to obtain an optimized buffer sequence; calculating the ratio of the total number of cached data packets in the buffer to the total buffer capacity based on the optimized buffer sequence to obtain the real-time occupancy rate; and performing a sliding average on the real-time occupancy rate within a continuous time window to obtain the network buffer occupancy rate.

[0063] Specifically, based on the calculated remaining bandwidth allocation, buffer resources are finely managed. Real-time buffer occupancy data is continuously extracted. When the occupancy exceeds a set threshold, such as 80%, it indicates excessive cache pressure, triggering a sliding window adjustment mechanism. This mechanism smooths the occupancy data over consecutive time periods to distinguish between short-term fluctuations and sustained high occupancy. For example, when the sliding average shows a persistently high occupancy rate, the buffer allocation ratio for large data packet groups is dynamically increased to accelerate data clearing and avoid congestion. Simultaneously, to eliminate the impact of traffic fluctuations, the real-time occupancy rate is calculated, for example: 4MB cached / 20MB total capacity = 20%, and a sliding average is applied. For example, averaging the sequence [18%, 20%, 22%, 25%, 21%] yields 21.2%, ultimately resulting in a stable and reliable network buffer occupancy rate indicator. Figure 2 The diagram shows bandwidth allocation and usage. While the real-time traffic of the initial response network sequence is bursty, its long-term average bandwidth usage is low, approximately 50Mbps. To ensure extremely low transmission latency and extremely high response priority, the system statically allocates 150Mbps of bandwidth to it. This allocation strategy is an oversupply guarantee mechanism, ensuring that critical business data can be transmitted instantly under any burst situation. However, in actual use, most of the pre-allocated bandwidth remains idle. Initial bandwidth allocation is performed for medium-stability data packet groups and high-volume data packet groups. Figure 2In the medium-stable data packet group, the traffic pattern is typically periodic and stable, such as regular data collection and device status synchronization. Based on its stable characteristics, approximately 300Mbps of bandwidth is allocated to it. The high-volume data packet group typically exhibits bursty and high-throughput demands, such as uploading video surveillance recordings or backing up batch log data; it is initially allocated approximately 350Mbps of bandwidth. Finally, in the dynamic adjustment phase, the bandwidth resource manager continuously monitors the actual bandwidth usage of each group. When the actual demand of the high-volume data packet group exceeds its initial allocation (e.g., 350Mbps), while the medium-stable data packet group still has unused bandwidth quota, the manager dynamically reallocates the idle bandwidth resources of the medium-stable data packet group to the high-volume data packet group to ensure smooth data transmission and avoid network congestion. This dynamic reallocation mechanism based on actual usage greatly improves the utilization efficiency of total bandwidth resources.

[0064] After dynamically adjusting the buffer, the actual usage of the buffer is quantitatively characterized by calculating the real-time occupancy rate. The real-time occupancy rate is the ratio of the total number of data packets cached in the buffer to the total buffer capacity at a given point in time, reflecting the immediate pressure on the buffer. Since the instantaneous occupancy rate may fluctuate due to sudden traffic spikes, the system performs a moving average over consecutive time windows to obtain a more stable occupancy rate indicator. If the system samples every 100ms and obtains five real-time occupancy rate values ​​of 18%, 20%, 22%, 25%, and 21%, the moving average occupancy rate is (18+20+22+25+21) / 5 = 21.2%. This method effectively offsets the impact of single-instance traffic spikes, more accurately reflects the stable occupancy status of the buffer, and ultimately provides a dynamic and smooth network buffer occupancy rate.

[0065] After generating the optimized buffer sequence, large-volume data packet groups are batch-packaged, aggregating data packets within the same time window to form optimized transmission blocks. Batch packaging not only reduces the processing overhead of individual data packets but also improves the transmission efficiency of large-volume data. For example, if several data packets with the same destination address are collected within a time window, they can be packaged into a large block for unified transmission, reducing protocol overhead. When the size of a transmission block exceeds a preset threshold, it is further split into multiple transmission sub-blocks to avoid sudden pressure on a single link. After the sub-blocks are generated, the real-time response network sequence is integrated with the transmission sub-blocks according to the sequence merging rules to form a merged data stream. The sequence merging rules include: prioritizing sorting according to the priority of data packets, aligning data from different sources based on timestamps, and prioritizing the transmission of the real-time response sequence during bandwidth contention. Through these rules, it is ensured that high-frequency small packets are not affected by delays due to the packaging of large-volume data, thereby maintaining overall real-time performance and stability. Finally, the merged data stream is further divided into multiple data stream segments, each segment is bound to specific bandwidth usage information and path identifiers for subsequent multi-path allocation and dynamic scheduling. This division method enables the system to achieve flexible scheduling and efficient transmission in complex building networks, ensuring the collaborative work and data interaction of different types of devices in a multi-protocol environment.

[0066] The optimized transport block obtained in step S4 includes:

[0067] If the network buffer occupancy rate is lower than a preset threshold, the existing scheduling is maintained; otherwise, the network buffer is determined to be in a high-occupancy state, and the resource allocation ratio is adjusted through a dynamic allocation algorithm to generate a ratio adjustment set. Based on the ratio adjustment set, a batch packaging method is used to integrate data packets for large-volume data packet groups to obtain optimized transport blocks.

[0068] Specifically, the distribution characteristics of network buffer occupancy are obtained, and it is determined whether the distribution characteristics of the occupancy feature set are lower than a preset threshold (e.g., 80%). If the current buffer occupancy is lower than the preset threshold, the buffer is still in a normal state, and there is no need to change the existing scheduling strategy. If the occupancy exceeds the preset threshold, it is determined that the network buffer is in a high-occupancy state, triggering a dynamic allocation algorithm. Based on the real-time occupancy and packet bandwidth requirements, the buffer ratio of different data packet groups is reallocated. For example, the buffer ratio of large-volume data packet groups is appropriately increased to speed up their data cleanup, thereby avoiding buffer overload. After the resource allocation adjustment is completed, the data packets already cached in the large-volume data packet groups are aggregated in a batch packaging method within a specified time window to reduce the frequency of single-packet scheduling and improve transmission efficiency. If the length of the generated transmission block exceeds the set maximum value, it will be further split into multiple sub-blocks to prevent a single block from causing a sudden impact on the link due to its excessive size.

[0069] In step S4, merging the real-time response network sequence with the transmission sub-blocks to form a merged data stream includes: arranging the data packets according to their priority order, aligning the timing based on the arrival timestamps of the data packets, prioritizing the transmission of the real-time response network sequence when bandwidth contention occurs in the same time period, setting sequence merging rules, and queuing and adjusting the sub-block network sequences to obtain the merged data packet sequence; dividing the merged data packet sequence into multiple data stream segments, each data stream segment corresponding to a bandwidth occupancy value and a transmission path identifier.

[0070] Specifically, sequence merging rules are set up according to data packet priority, time-series alignment based on data packet arrival timestamps, and prioritizing real-time response network sequence transmission when bandwidth contention occurs within the same time period. In detail, data packets are first arranged according to priority, which can be determined based on service type, real-time requirements, or preset tags. For example, voice and video data packets are usually assigned higher priority, while large-volume file transfer data packets have relatively lower priority. This order ensures that more important service data is not delayed due to low-priority traffic during the merging process. After priority sorting, time-series alignment is required based on data packet arrival timestamps. Because different data packets... During data acquisition and transmission, slight arrival deviations may occur. By uniformly correcting timestamps, the continuity of the merged data sequence in the time dimension can be guaranteed, avoiding network jitter or decoding difficulties caused by out-of-order delivery. When multiple data packets need to be transmitted within the same time period, the merging rules further require prioritizing the transmission of the real-time response network sequence. This means that when bandwidth is insufficient, short, high-frequency data packets will occupy transmission resources first, while large-volume sub-blocks will be appropriately delayed or processed in batches to maintain the overall stability of the system and the real-time performance of critical services. During this process, transmission sub-blocks will be queued and adjusted according to the rules, reordered, and merged with the real-time response sequence to form a merged complete data packet sequence. The merged data packet sequence will be further divided into multiple data stream segments, each corresponding to an independent bandwidth usage value and transmission path identifier. The division criteria are mainly based on bandwidth requirements and path resources. For example, data stream segments with high bandwidth requirements (such as large-volume network packet groups) will be allocated more bandwidth, while segments with lower bandwidth requirements (such as short, high-frequency packet groups) will be allocated less bandwidth. The bandwidth usage value is calculated based on the size and number of packets contained in the segment. The transmission path identifier is used to indicate which network path the segment will be transmitted through. Different network paths can be optimized based on network load and bandwidth conditions to ensure efficient transmission. Through mechanisms such as priority queue scheduling, timing alignment, sequence merging rules, and bandwidth resource allocation, it is ensured that each packet and data stream segment can be transmitted efficiently according to real-time network conditions.

[0071] Step S5: Assign a network transmission path to each data stream segment, monitor the bandwidth usage and transmission delay of each transmission path in real time, and dynamically adjust the path allocation and network buffer resources of the data stream segments based on the monitoring results to complete the data transmission.

[0072] Step S5 further includes: allocating data stream segments to multiple independent network paths through a multipath transmission protocol to obtain a multipath allocation set; based on the multipath allocation set, continuously monitoring the transmission delay of each network path using a sliding window method, extracting network delay values ​​and forming a delay distribution sequence; if the network delay value of a path in the delay distribution sequence exceeds a preset threshold, then calling a dynamic routing adjustment algorithm to reallocate the data stream segments of the network path to form an optimized path set; and according to the optimized path set, reallocating network buffer resources using a weighted average method to output an updated buffer optimization sequence.

[0073] Specifically, based on a multipath transmission protocol, each data stream segment is assigned to multiple independent network paths. Through this protocol, data stream segments can utilize multiple paths simultaneously for transmission, improving bandwidth utilization and redundancy. If multiple available transmission paths exist in the network environment, such as different network interfaces or wireless / wired paths, data stream segments are allocated paths based on criteria such as bandwidth, latency, and network load to ensure balanced transmission across different paths. While data stream segments are transmitted through multiple paths, the transmission latency of each path is monitored in real time. During monitoring, the latency value of each path is extracted and recorded, forming a latency distribution sequence. To ensure timely data transmission, a sliding window method is used to continuously monitor latency. This method collects latency data within a fixed time window and dynamically updates the window content over time, thereby tracking latency changes across each network path. Figure 3The diagram illustrates network path latency and dynamic routing adjustment. It shows the latency values ​​for paths 1 through 4 and compares them to preset latency thresholds. The dots in the diagram represent the latency value for each path, and the dashed line (red) represents the latency threshold. If the latency of a path exceeds this threshold, it indicates a potential network problem or overload on that path, necessitating a dynamic routing adjustment algorithm to select a better path or adjust data flow allocation. When the latency of a path exceeds the set threshold, such as path 2, the dynamic routing adjustment mechanism is triggered. At this time, the system can automatically adjust the data flow path selection, choosing paths with lower latency, such as path 1 or path 3, to optimize network performance and data transmission speed. During the dynamic adjustment process, the system recalculates and selects the most suitable transmission path based on latency distribution data and network load, ensuring data real-time performance and network stability. This method allows for accurate understanding of path latency characteristics and timely detection of potential problems. A dynamic routing adjustment algorithm is employed to migrate data stream segments from paths with excessive latency to other, more efficient paths. This process selects the most suitable path based on the real-time network status, taking into account not only latency but also bandwidth and load, thereby ensuring low latency and high efficiency in data transmission. After path adjustment, an optimized path set is generated, containing all adjusted network paths. Based on this path set, network buffer resources are reallocated using a weighted averaging method. This method considers the bandwidth utilization, latency, and load of each path, allocating buffer resources rationally. For example, if a path has high bandwidth utilization, its buffer resource allocation is reduced to ensure that other paths receive sufficient buffer support, thus improving the overall network performance and stability. After buffer resource reallocation, an optimized buffer resource sequence is generated to support subsequent data stream transmission, ensuring efficient data transmission under different paths and loads.

[0074] The above describes a method for multi-protocol compatibility of intelligent building low-voltage electrical equipment in an embodiment of this application. The following describes a system for multi-protocol compatibility of intelligent building low-voltage electrical equipment in an embodiment of this application. Please refer to [link to relevant documentation]. Figure 4 One embodiment of a multi-protocol compatible system for intelligent building low-voltage electrical equipment in this application includes:

[0075] The acquisition module is used to acquire the multi-protocol network data stream of low-voltage equipment in intelligent buildings, extract the length value and arrival interval of each network data packet from the multi-protocol network data stream, and form network classification features.

[0076] The first segmentation module is used to classify network data packets into short, high-frequency network data packet groups, medium-stability network data packet groups, and high-volume network data packet groups based on network classification characteristics.

[0077] The calculation module is used to prioritize the transmission of data packets in short, high-frequency network data packet groups through a priority queue scheduling mechanism to form a real-time response network sequence. Based on the transmission status of the real-time response network sequence, it calculates the remaining bandwidth for transmitting medium-stable network data packet groups and high-volume network data packet groups.

[0078] The second partitioning module is used to adjust the network buffer occupancy rate based on the remaining bandwidth, and to perform batch packaging of large-volume network data packets to generate optimized transmission blocks. When the length of the optimized transmission block exceeds the preset value, the optimized transmission block is split into multiple transmission sub-blocks. Based on the sequence merging rules, the real-time response network sequence and the transmission sub-blocks are merged to form a merged data stream, and the merged data stream is divided into multiple data stream segments.

[0079] The adjustment module is used to allocate network transmission paths for each data stream segment, monitor the bandwidth usage and transmission latency of each transmission path in real time, and dynamically adjust the path allocation and network buffer resources of the data stream segments based on the monitoring results to complete data transmission.

[0080] This application also provides a computer-readable storage medium, which can be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium. The computer-readable storage medium stores instructions that, when executed on a computer, cause the computer to perform the steps of the multi-protocol compatibility method for intelligent building low-voltage electrical equipment.

[0081] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0082] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0083] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A method for multi-protocol compatibility of intelligent building weak current equipment, characterized in that, The method comprises: Step S1, obtaining the multi-protocol network data stream of the weak current equipment in the intelligent building, extracting the length value and the arrival interval time of each network data packet from the multi-protocol network data stream to form network classification features; Step S2, based on the network classification features, classifying the network data packets into a small high-frequency network data packet group, a medium stable network data packet group and a large flow network data packet group; Step S3, through a priority queue scheduling mechanism, preferentially scheduling and transmitting the data packets in the small high-frequency network data packet group to form a real-time response network sequence, and based on the transmission of the real-time response network sequence, calculating the remaining bandwidth for transmitting the medium stable network data packet group and the large flow network data packet group; Step S4, based on the remaining bandwidth, adjusting the network buffer occupancy rate, and performing batch packaging processing on the large flow network data packet group to generate an optimized transmission block, when the length of the optimized transmission block exceeds a preset value, splitting the optimized transmission block into multiple transmission sub-blocks, merging the real-time response network sequence and the transmission sub-blocks based on sequence merging rules to form a merged data stream, and dividing the merged data stream into multiple data stream segments; Step S5, assigning a network transmission path to each data stream segment, and monitoring the bandwidth occupancy and transmission delay of each transmission path in real time, and dynamically adjusting the path allocation of the data stream segment and the network buffer resource according to the monitoring result to complete data transmission.

2. The method of claim 1, wherein, The network classification features formed in step S1 include: Calculating the mean value of the network data packet length value and the standard deviation of the data packet arrival interval time, and taking the mean value and the standard deviation as the network classification features.

3. The method of claim 1, wherein, Step S2 includes: Using a clustering algorithm to group the network data packets to obtain a preliminary grouping result; Based on the protocol type and flow distribution characteristics of each group in the preliminary grouping result, a classification model is used to identify and confirm the small high-frequency network data packet group, the medium stable network data packet group and the large flow network data packet group.

4. The method of claim 1, wherein, The formation of the real-time response network sequence in step S3 includes: For the small high-frequency data packet group, the data packets in the group are sorted based on the arrival time, priority label and emergency degree of the data packets to generate a priority queue scheduling mechanism, and the transmission order of the data packets is adjusted to generate an initial response network sequence; Based on the initial response network sequence, the timing characteristics of the small high-frequency data packet group are extracted, the transmission stability of the data packets is judged based on the timing characteristics, and a stable transmission sequence is determined; From the stable transmission sequence, the transmission interval distribution of the small high-frequency data packet group is obtained, the transmission interval distribution is compared with a preset threshold value, and if the threshold value condition is met, the stable transmission sequence is determined as the real-time response network sequence; If the threshold value condition is not met, the scheduling strategy of the priority queue scheduling mechanism is adjusted based on the stable transmission sequence until the threshold value condition is met to determine the real-time response network sequence.

5. The method of claim 1, wherein, In step S4, adjusting the network buffer occupancy rate based on the remaining bandwidth resource includes: According to the real-time response network sequence, bandwidth occupancy of the medium stable data packet group and the large flow data packet group is analyzed, a remaining bandwidth resource is calculated by using a weighted average method, and a bandwidth allocation set is determined; Real-time occupancy data of a network buffer is extracted through the bandwidth allocation set; If the real-time occupancy data exceeds a preset threshold, a sliding window method is used to adjust a dynamic adjustment buffer allocation ratio between the data packet groups, and an optimized buffer sequence is obtained; A real-time occupancy rate is obtained according to a ratio of a total amount of cached data packets in the buffer to a total capacity of the buffer according to the optimized buffer sequence, and a sliding average of the real-time occupancy rate is performed in a continuous time window to obtain a network buffer occupancy rate.

6. The method of claim 5, wherein, The optimized transmission block obtained in step S4 includes: If the network buffer occupancy rate is lower than a preset threshold, the existing scheduling is maintained, otherwise, it is determined that the network buffer is in a high occupancy state, and a resource allocation ratio is adjusted through a dynamic allocation algorithm to generate a ratio adjustment set; According to the ratio adjustment set, data packets are integrated by using a batch packaging method for the large flow data packet group to obtain an optimized transmission block.

7. The method of claim 1, wherein, The merging of the real-time response network sequence and the transmission sub-block in step S4 to form a merged data stream includes: The sequence merging rule is that the data packets are arranged in order of priority, time alignment is performed based on a data packet arrival timestamp, and transmission of the real-time response network sequence is preferentially ensured when bandwidth competition occurs at the same time period, and the sub-block network sequence is adjusted in a queue to obtain a merged data packet sequence; The merged data packet sequence is divided into multiple data stream segments, and each data stream segment corresponds to a bandwidth occupancy value and a transmission path identifier.

8. The method of claim 1, wherein, Step S5 includes: The data stream segments are distributed to multiple independent network paths through a multi-path transmission protocol to obtain a multi-path distribution set; Based on the multi-path distribution set, a sliding window method is used to continuously monitor transmission delays of each network path, network delay values are extracted, and a delay distribution sequence is formed; If the network delay value of a path in the delay distribution sequence exceeds a preset threshold, a dynamic routing adjustment algorithm is called to re-distribute the data stream segments of the network path to form an optimized path set; According to the optimized path set, a weighted average method is used to re-distribute network buffer resources, and an updated buffer optimization sequence is output.

9. A multi-protocol compatible system for intelligent building weak current equipment, which is used for implementing the multi-protocol compatible method for intelligent building weak current equipment according to any one of claims 1-8, characterized in that, The system includes: An acquisition module is configured to acquire multi-protocol network data streams of weak current equipment in an intelligent building, extract a length value and an arrival interval time of each network data packet from the multi-protocol network data streams, and form network classification features; A first division module is configured to classify the network data packets into a small high-frequency network data packet group, a medium stable network data packet group, and a large flow network data packet group based on the network classification features; A calculation module is configured to form a real-time response network sequence by preferentially scheduling and transmitting data packets in the small high-frequency network data packet group through a priority queue scheduling mechanism, and calculate a remaining bandwidth for transmitting the medium stable network data packet group and the large flow network data packet group based on transmission of the real-time response network sequence. The second dividing module is configured to adjust network buffer occupancy based on the residual bandwidth, perform batch packaging processing on the large-flow network data packet group, generate an optimized transmission block, split the optimized transmission block into a plurality of transmission sub-blocks when the length of the optimized transmission block exceeds a preset value, merge the real-time response network sequence and the transmission sub-blocks based on a sequence merging rule to form a merged data stream, and divide the merged data stream into a plurality of data stream segments. The adjusting module is configured to allocate a network transmission path to each data stream segment, monitor bandwidth occupancy and transmission delay of each transmission path in real time, and dynamically adjust path allocation of the data stream segment and network buffer resources according to the monitoring result to complete data transmission.

10. A computer-readable storage medium having stored thereon instructions, the instructions comprising, The instructions are executed by the processor to implement the intelligent building weak current equipment multi-protocol compatible method of any one of claims 1-8.

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