Internet of Things data information transmission method, switch and transmission system

Abstract

The invention relates to the technical field of Internet of Things communication, and discloses an Internet of Things data information transmission method, a switch and a transmission system. The method comprises the following steps: acquiring multi-source data streams of Internet of Things terminal equipment, dynamically fragmenting according to types to generate fragmented data packets, matching a target transmission protocol for the fragmented data packets, generating a dynamic routing path in combination with a priority mark and the like, and transmitting the dynamic routing path. The system also has the functions of link quality evaluation and route adjustment, redundant coding packet loss recovery, transmission delay and integrity monitoring processing, encryption transmission based on security level, resource optimization, transmission strategy adjustment and the like. The switch is integrated with a data fragmentation module, a protocol matching module and the like. The transmission system comprises a terminal device cluster, an edge node network, a cloud server and a protocol conversion gateway. The data transmission efficiency, reliability and safety are improved, resource utilization is optimized, and the data transmission problem of the Internet of Things is effectively solved.

Description

Technical Field

[0001] The present invention relates to the technical field of Internet of Things communication, and particularly to a method for transmitting Internet of Things data information, a switch, and a transmission system. Background Art

[0002] In today's digital age, the Internet of Things technology has been booming and widely applied in many fields such as smart home, industrial monitoring, and intelligent transportation. With the rapid increase in the number of Internet of Things devices and the increasing complexity of application scenarios, data information transmission is facing many severe challenges.

[0003] Different types of Internet of Things terminal devices will generate diverse data, such as sensor data, video streams, and control instructions. Sensor data usually has the characteristics of small data volume and strong periodicity; video stream data volume is huge, and it has extremely high requirements for real-time and continuity; control instructions are extremely sensitive to transmission delay and need to ensure timely and accurate delivery to the target device. However, existing transmission methods often adopt a unified processing method and cannot be optimized according to the characteristics of different types of data, resulting in low transmission efficiency and inability to meet actual needs. For example, in a smart home system, the temperature and humidity data collected by sensors may have transmission delays due to the same transmission strategy as a large amount of video stream data, unable to timely feedback the indoor environment changes and affecting the user experience.

[0004] The Internet of Things network environment is complex and changeable, and network state parameters such as bandwidth utilization rate, packet loss rate, and jitter value are constantly in dynamic change. The traditional static routing method is difficult to adapt to this complex network environment and cannot adjust the data transmission path according to the real-time network condition. When a certain link appears congested or fails, data is easily lost or the transmission delay increases significantly, seriously affecting the reliability of data transmission. In the industrial Internet of Things, once the network failure causes the transmission delay of control instructions, it may lead to abnormal operation of production equipment and cause huge economic losses.

[0005] Data security and privacy protection are crucial in the field of the Internet of Things. Internet of Things data contains a large amount of sensitive information, such as personal identity information, enterprise production data, etc. Most existing data encryption methods use fixed keys or simple encryption algorithms, which are difficult to resist increasingly complex network attacks. Moreover, during the data transmission process, there is a lack of an effective key management mechanism, unable to ensure the secure distribution and update of keys, increasing the risk of data leakage. For example, in a smart medical system, if the medical record data of patients is stolen during the transmission process, it will seriously violate the privacy of patients.

[0006] In addition, the edge nodes and terminal devices in the Internet of Things system have limited resources. The computing resources and storage capacity of edge nodes often cannot meet the requirements of all data processing and storage, and the power of terminal devices is also very precious. Existing transmission methods rarely consider the optimal utilization of resources, resulting in a decline in performance of some edge nodes due to excessive load, and terminal devices need to frequently replace batteries or charge due to excessive energy consumption, increasing the maintenance cost and inconvenience of use. In smart agriculture, a large number of sensor nodes are distributed in farmland. If the transmission strategy cannot be reasonably optimized to reduce energy consumption, the batteries need to be frequently replaced, which brings great trouble to practical applications. Summary of the Invention

[0007] The purpose of the present invention is to provide an Internet of Things data information transmission method, a switch, and a transmission system to solve the problems proposed in the above background technology.

[0008] To achieve the above purpose, the present invention provides the following technical solutions: An Internet of Things data information transmission method, the method includes:

[0009] Real-time obtain multi-source data streams of Internet of Things terminal devices, the multi-source data streams include sensor data, video streams, and control instructions;

[0010] Dynamically fragment the multi-source data streams based on the data stream type to generate fragmented data packets; the dynamic fragmentation includes: adopting fixed-length fragmentation for sensor data, adopting fragmentation based on inter-frame correlation for video streams, and adopting priority marking fragmentation for control instructions;

[0011] According to a preset set of transmission protocols, match a target transmission protocol for each fragmented data packet; the set of transmission protocols includes: MQTT, CoAP, and a custom low-latency protocol;

[0012] Bind the fragmented data packets with the matched target transmission protocols, and generate a dynamic routing path based on the priority marking of the fragmented data packets; the dynamic routing path is determined by calculating the delay sensitivity, link load rate, and hop count constraint of the fragmented data packets;

[0013] Transmit the fragmented data packets bound with the target transmission protocols along the dynamic routing path to the target edge node or cloud server.

[0014] Preferably, the Internet of Things data information transmission method further includes:

[0015] Real-time monitor the network state parameters of each transmission link, including bandwidth utilization rate, packet loss rate, and jitter value;

[0016] Construct a link quality evaluation model, which is trained by the relationship between historical network state parameters and transmission success rate;

[0017] Input the current network status parameters into the link quality assessment model to output the dynamic weight values of each transmission link;

[0018] Adjust the dynamic routing path of the fragmented data packets according to the dynamic weight values, and preferentially select the links with weight values higher than the preset threshold.

[0019] Preferably, the method for transmitting IoT data information further includes:

[0020] When the target transmission protocol of the fragmented data packet is a custom low-latency protocol, perform redundant encoding on the fragmented data packet to generate redundant check blocks;

[0021] Insert at least one backup node into the dynamic routing path and distribute the redundant check blocks to the backup nodes;

[0022] If it is detected that the packet loss rate of the main transmission path exceeds the preset threshold, trigger the backup nodes to recover the lost fragmented data packets based on the redundant check blocks.

[0023] Preferably, the method for transmitting IoT data information further includes:

[0024] During the transmission process, statistically record the transmission delay and integrity index of each fragmented data packet in real time;

[0025] If the transmission delay difference of the fragmented data packets of the same data stream exceeds the preset delay tolerance, perform local caching and recombination on the unarrived fragmented data packets and trigger a retransmission request;

[0026] If the integrity index of the fragmented data packet is lower than the preset threshold, perform data repair according to the redundant check blocks or historical fragmented data.

[0027] Preferably, the method for transmitting IoT data information further includes:

[0028] Divide the security levels of the data streams according to the types and service scenarios of the IoT terminal devices;

[0029] Perform dynamic encryption on the fragmented data packets with security levels higher than the preset threshold, and the dynamic encryption includes: generating a temporary key based on the generation timestamp of the fragmented data packet and the unique device identifier;

[0030] Designate at least one encryption relay node in the dynamic routing path for performing the distribution and update of the temporary key.

[0031] Preferably, the method for transmitting IoT data information further includes:

[0032] Statistically record the computing resource utilization rate and remaining storage capacity of each edge node;

[0033] If the target transport protocol of the sharded data packet is a video stream protocol and the computing resource utilization rate of the edge node is lower than the preset threshold, route the sharded data packet to the edge node for real-time video analysis;

[0034] Otherwise, route the sharded data packet to the cloud server.

[0035] Preferably, the method for transmitting Internet of Things data information further includes:

[0036] Collect the protocol conversion times and routing hops of the sharded data packet during the transmission process;

[0037] If the protocol conversion times exceed the preset times or the routing hops exceed the preset hops, trigger the aggregation operation of the sharded data packet, merge multiple sharded data packets into an aggregated data block, and switch to a high-bandwidth transport protocol for transmission.

[0038] Preferably, the method for transmitting Internet of Things data information further includes:

[0039] Build an energy consumption model for each Internet of Things terminal device, and the energy consumption model is trained through the relationship between historical transmission power consumption and data volume;

[0040] Predict the transmission energy consumption according to the size of the current sharded data packet and the target transport protocol;

[0041] If the predicted energy consumption exceeds the remaining power threshold of the terminal device, switch to the low-power transmission mode, and the low-power transmission mode includes reducing the transmission frequency or enabling compression coding.

[0042] Preferably, the present invention further includes a switch, including:

[0043] A data sharding module, configured to dynamically shard multi-source data streams based on the data stream type to generate sharded data packets;

[0044] A protocol matching module, configured to match a target transport protocol for the sharded data packet according to the transport protocol set;

[0045] A routing calculation module, configured to generate a dynamic routing path based on the priority marking of the sharded data packet and the network status parameters;

[0046] A transmission execution module, configured to transmit the sharded data packet bound with the target transport protocol along the dynamic routing path;

[0047] A redundancy processing unit, configured to generate a redundancy check block for the sharded data packet of the custom low-latency protocol and manage the backup nodes.

[0048] Preferably, the present invention further includes an Internet of Things data transmission system, and the system includes:

[0049] A cluster of terminal devices, used to generate multi-source data streams and execute a method for transmitting Internet of Things data information;

[0050] An edge node network, used to receive sharded data packets and perform real-time analysis or forwarding;

[0051] A cloud server, used to store aggregated data blocks and provide global resource scheduling;

[0052] A protocol conversion gateway, used to perform adaptive conversion between different transmission protocols and unify data formats.

[0053] Compared with the prior art, the beneficial effects of the present invention are:

[0054] In terms of data transmission efficiency, dynamic sharding is performed for different types of multi-source data streams. For example, sensor data is sharded with a fixed length, video streams are sharded based on inter-frame correlation, and control instructions are sharded with priority tags. This can make full use of the characteristics of various types of data and improve the efficiency of data processing and transmission. At the same time, according to the preset set of transmission protocols, the target transmission protocol is matched for the sharded data packets, combined with the generation of dynamic routing paths, and factors such as delay sensitivity, link load rate, and hop count constraints are comprehensively considered to ensure that data can be quickly and efficiently transmitted to the target node. For example, in an intelligent transportation system, vehicle driving status data (sensor data) can be quickly transmitted through a suitable protocol and routing, and traffic monitoring video streams can also be reasonably processed and transmitted, ensuring the timely acquisition and processing of traffic information and effectively improving the data transmission efficiency of the entire system.

[0055] In terms of transmission reliability, the network state parameters of each transmission link are monitored in real time, and a link quality evaluation model is constructed. According to the evaluation results, the routing path is adjusted, and links with good quality are preferentially selected, greatly reducing data loss and delay problems caused by link failures or congestion. For sharded data packets using a custom low-latency protocol, redundant coding is performed and backup nodes are set. When a high packet loss rate occurs on the main transmission path, the lost data can be recovered through the backup nodes, ensuring data integrity and transmission reliability. On an industrial automation production line, the transmission of key control instructions and equipment operation data is guaranteed, reducing production accidents and losses caused by data transmission problems.

[0056] In terms of data security, the data stream security level is divided according to the types of Internet of Things terminal devices and business scenarios. Sharded data packets with a high security level are dynamically encrypted. A temporary key is generated based on the generated timestamp and the unique device identifier, and the key is distributed and updated through an encrypted relay node, effectively preventing data from being stolen or tampered with during transmission. In the field of financial Internet of Things, when transmitting user account information and transaction data, this encryption method greatly improves data security and protects the property security and privacy of users.

[0057] From the perspective of optimizing resource utilization, the computing resource utilization rate of edge nodes and the remaining storage capacity are statistically analyzed, and processing tasks are reasonably allocated according to the situation of video stream protocol data packets. Real-time video analysis is performed when the resources of edge nodes are sufficient, otherwise it is transmitted to the cloud server, realizing the efficient utilization of computing resources. At the same time, the transmission energy consumption is predicted according to the energy consumption model of terminal devices. When the predicted energy consumption exceeds the remaining power threshold, the low-power transmission mode is switched, extending the service life of terminal devices and reducing the maintenance cost. In an intelligent security monitoring system, a large number of monitoring cameras are used as terminal devices. In this way, while ensuring the monitoring effect, the device energy consumption can be reduced and the overall operation efficiency of the system can be improved.

[0058] In addition, during the transmission process, the number of protocol conversions and the number of routing hops are monitored. When they exceed the preset values, the aggregation operation of fragmented data packets is triggered and the high-bandwidth transmission protocol is switched, reducing the transmission overhead and improving the transmission performance. Through the above multi-faceted optimizations, the present invention comprehensively improves the quality and efficiency of Internet of Things data transmission, effectively solves the problems existing in the prior art, and has broad application prospects and great economic value. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 is the working principle diagram of the Internet of Things data information transmission method described in the present invention;

[0060] Figure 2 is the working flow chart of adjusting the routing based on link quality assessment;

[0061] Figure 3 is the working flow chart of monitoring and processing transmission delay and integrity;

[0062] Figure 4 is the working flow chart of encrypted transmission based on security level. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0063] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0064] Please refer to Figures 1-4 , the present invention proposes an Internet of Things data information transmission method, and the method includes:

[0065] Real-time acquisition of multi-source data streams: Through Internet of Things (IoT) terminal devices, various types of data are collected in real time to form multi-source data streams. These data include various environmental data collected by sensors, such as sensor data like temperature, humidity, and light intensity; video streams generated by monitoring cameras; and control instructions issued by users or systems. Taking the smart home scenario as an example, a smart temperature sensor continuously collects indoor temperature data as sensor data; a smart camera captures indoor images in real time to form a video stream; and a user sends an instruction to adjust the indoor temperature through a mobile APP as a control instruction.

[0066] Dynamically slice and generate data packets: According to different types of data streams, different slicing strategies are adopted. For sensor data, since the data volume is relatively small and stable, a fixed-length slicing method is used. For example, if the fixed length is set to 1024 bytes, the sensor data is cut according to this length to facilitate subsequent unified processing and transmission. For video streams, due to their large data volume and correlation between frames, slicing is based on the inter-frame correlation. Several consecutive frames with little change can be divided into a slice according to the degree of change of video frames to reduce transmission redundancy. For control instructions, because of their extremely high requirement for timeliness, priority marking slicing is used to ensure the priority transmission of important instructions.

[0067] Match the target transmission protocol: From the preset set of transmission protocols, the most suitable target transmission protocol is selected for each sliced data packet. This set of transmission protocols includes MQTT, CoAP, and a custom low-latency protocol, etc. The MQTT protocol is suitable for scenarios with relatively low requirements for real-time performance, small data volume, and relatively stable network environments, such as the regular reporting of sensor data. The CoAP protocol is more suitable for resource-constrained IoT devices and transmits data in a lightweight manner. The custom low-latency protocol is designed specifically for control instructions and key data that are sensitive to latency. In practical applications, if the sliced data packet is sensor data and the network environment is stable, the MQTT protocol can be selected; if it is a control instruction, the custom low-latency protocol is selected.

[0068] Generate a dynamic routing path: Bind the sliced data packet to the matched target transmission protocol, and based on the priority marking of the sliced data packet, comprehensively calculate factors such as the latency sensitivity, link load rate, and hop count constraint of the data packet to generate a dynamic routing path. For data packets with high latency sensitivity, preferentially select links with low latency; for the link load rate, monitor the load conditions of each link in real time and avoid selecting links with too high load to ensure transmission efficiency. For example, if a sliced data packet of a control instruction has high latency sensitivity, and currently in the network, link A has a low load rate, few hops, and low latency, while link B has a high load rate, many hops, and high latency, then link A is preferentially selected as the routing path.

[0069] Data transmission to the target node: According to the generated dynamic routing path, the sharded data packets bound to the target transmission protocol are transmitted to the target edge node or cloud server. In the smart home scenario, the sensor data sharded data packets may be first transmitted to the nearby edge node for preliminary processing, while the video stream sharded data packets may be directly transmitted to the cloud server for storage and analysis, and the control instruction sharded data packets are quickly transmitted to the edge node where the corresponding execution device is located to achieve timely control of the device.

[0070] The present invention will be further described below in conjunction with Embodiments 1 to 5:

[0071] Embodiment 1:

[0072] In this embodiment, by real-time monitoring the network status, constructing a link quality evaluation model, and adjusting the routing path according to the evaluation results, the reliability and stability of data transmission are improved, effectively coping with the dynamic changes of the network environment.

[0073] In the actual application scenario, taking the industrial Internet of Things production line as an example, numerous Internet of Things terminal devices such as sensors and actuators transmit data through the network. To realize the adjustment of the routing based on the link quality evaluation, the specific operations are as follows:

[0074] Real-time monitoring of network status parameters: Using network monitoring tools, the network status parameters of each transmission link are obtained in real time, including bandwidth utilization rate, packet loss rate, and jitter value. Data is collected at regular time intervals (such as every 5 seconds) to form a real-time monitoring data sequence. For example, at a certain moment, it is monitored that the bandwidth utilization rate of Link 1 is 60%, the packet loss rate is 2%, and the jitter value is 5 ms; the bandwidth utilization rate of Link 2 is 30%, the packet loss rate is 1%, and the jitter value is 3 ms.

[0075] Constructing a link quality evaluation model: Collect a large amount of historical network status parameters and the corresponding transmission success rate data. Assume that the historical data contains the network status parameters collected every 5 seconds in the past week and the records of whether the data transmission is successful. Using machine learning algorithms, such as linear regression algorithms, to train and construct a link quality evaluation model. Let the network status parameters be x1 (bandwidth utilization rate), x2 (packet loss rate), x3 (jitter value), and the transmission success rate be y. Through training, the model formula is obtained as y = a1x1 + a2x2 + a3x3 + b, where a1, a2, and a3 are the coefficients obtained from model training, and b is a constant term.

[0076] Calculating the dynamic weight value: Input the currently collected network status parameters into the link quality evaluation model to calculate the dynamic weight values of each transmission link. Taking the parameters of Link 1 and Link 2 monitored just now as an example, let x 11 = 60%, x 21 = 2%, x 31Substitute \(x = 5ms\) into the model to calculate the weight value \(y1\) of link 1; substitute \(x\) 12 \(= 30\%\), \(x\) 22 \(= 1\%\), \(x\) 32 \(= 3ms\) into the model to calculate the weight value \(y2\) of link 2.

[0077] Adjust the routing path: According to the calculated dynamic weight values, adjust the dynamic routing path of the fragmented data packets. Preset a weight threshold, such as 0.6. If the weight value \(y1\) of link 1 is lower than the threshold, while the weight value \(y2\) of link 2 is higher than the threshold, then preferentially select link 2 as the transmission link for subsequent fragmented data packets to ensure that data can be transmitted more reliably and reduce data loss or transmission delay problems caused by poor link quality.

[0078] Embodiment 2:

[0079] In this embodiment, for fragmented data packets using a custom low-latency protocol, through redundant coding and backup node settings, lost data can be quickly recovered in the case of network packet loss, ensuring data integrity and transmission reliability, and is particularly suitable for application scenarios with extremely high requirements for data integrity.

[0080] Taking the power monitoring system of a smart grid as an example, the real-time transmitted power data has extremely high requirements for accuracy and timeliness. In this scenario, the implementation of packet loss recovery based on redundant coding is as follows:

[0081] Generate redundant check blocks by redundant coding: When the target transmission protocol of the fragmented data packet is a custom low-latency protocol, use redundant coding techniques such as erasure codes to process the fragmented data packet. Assume that the size of the fragmented data packet is \(N\) bytes, and use \((n,k)\) erasure codes, where \(n\) is the total number of blocks generated after coding, \(k\) is the number of original data blocks, and \(n>k\). For example, select \((5,3)\) erasure codes to encode the original 3 fragmented data packets into 5 blocks, where 3 are original data blocks and 2 are redundant check blocks.

[0082] Insert backup nodes and distribute redundant check blocks: Select at least one suitable node as a backup node in the dynamic routing path. For example, select a stable node in the middle of the path from the data source to the target node as a backup node. Distribute the generated redundant check blocks to the backup nodes for storage. For example, send the above-generated 2 redundant check blocks to the selected backup node for preservation.

[0083] Packet Loss Detection and Recovery: Monitor the packet loss situation of the main transmission path in real time, and preset a packet loss rate threshold, such as 5%. If the detected packet loss rate of the main transmission path exceeds this threshold, for example, the actual packet loss rate reaches 8%, then trigger the backup node to recover the lost sharded data packets based on the redundant check blocks. The backup node uses the received redundant check blocks and the remaining correct sharded data packets, and through the decoding algorithm of erasure codes, calculates and recovers the lost sharded data packets, and then sends the recovered data to the target node to ensure the integrity of the data and avoid power monitoring system failures or misjudgments caused by data loss.

[0084] Embodiment 3:

[0085] Unique function of this embodiment: This embodiment monitors the transmission delay and integrity indicators of sharded data packets in real time, discovers and processes problems that occur during the transmission in a timely manner, ensures that the sharded data packets of the same data stream can reach the target node orderly and completely, and improves the quality and availability of data transmission.

[0086] In the intelligent transportation system, data interactions frequently occur between vehicles and roadside infrastructure, such as vehicle position information, driving speed, etc. Under this scenario, the implementation of transmission delay and integrity monitoring and processing is as follows:

[0087] Real-time statistics of transmission delay and integrity indicators: During the data transmission process, add a timestamp to each sharded data packet to record its sending time t send and receiving time t receive , and calculate the transmission delay by calculating t delay =t receive -t send At the same time, verify the received sharded data packets. For example, use the CRC verification algorithm to calculate the integrity indicator. For example, a data stream of a certain vehicle position information contains 10 sharded data packets, and the transmission delay and integrity verification results of each data packet are recorded in sequence at the receiving end.

[0088] Handling the problem of excessive transmission delay differences: Preset a delay tolerance, such as 50ms. If the transmission delay differences of the sharded data packets of the same data stream exceed this tolerance, for example, the delay of one sharded data packet is 30ms and the other is 100ms, exceeding the 50ms tolerance, then perform local cache reorganization on the unarrived sharded data packets. Temporarily store the arrived sharded data packets in the local cache and wait for other sharded data packets to arrive for reorganization. At the same time, trigger a retransmission request and send a retransmission instruction to the sending end to request the retransmission of the sharded data packets with too long delay or lost to ensure the orderly arrival of the data.

[0089] Handling the problem that the processing integrity index is lower than the threshold: Preset an integrity threshold, such as 95% (indicating that a certain proportion of verification errors are allowed). If the integrity index of the sharded data packet is lower than this threshold, for example, the integrity verification result shows that only 90% of the data packets are verified correctly, data repair is performed according to the redundant verification block or historical sharded data. If redundant encoding was previously used to generate a redundant verification block, at this time, the redundant verification block and the correctly received sharded data packets are used to repair the error data through the corresponding decoding algorithm; if there is no redundant verification block, the sharded data of the same data stream in the historical transmission record is searched, and the correct data is obtained from it for repair to ensure the integrity of the data and provide reliable data support for the accurate decision-making of the intelligent transportation system.

[0090] Example 4:

[0091] In this example, the security level of the data stream is divided according to the type of IoT terminal device and the business scenario. The data with a high security level is dynamically encrypted, and the secure distribution and update of the key are ensured through the encrypted relay node, effectively protecting the security and privacy of the data during the transmission process.

[0092] In the financial IoT scenario, such as the data transmission between a bank automated teller machine (ATM) and a bank server, a large amount of sensitive user account information and transaction data are involved. For this scenario, encrypted transmission based on the security level is implemented, and the specific operations are as follows:

[0093] Dividing the security level of the data stream: According to the business requirements and data sensitivity of the ATM device, the data stream is divided into different security levels. For example, data such as the user's account password and transaction amount are divided into a high security level; the device's operating status information and general transaction records are divided into a medium security level; the device's software update notification, etc. are divided into a low security level. Preset a security level threshold, such as setting the high security level above the threshold and the medium and low security levels below the threshold.

[0094] Dynamic encryption processing: For the sharded data packets with a security level higher than the preset threshold, that is, the data with a high security level, dynamic encryption is performed. A temporary key is generated based on the generation timestamp t of the sharded data packet and the device unique identifier ID. Using a hash function, such as the SHA-256 algorithm, calculate the temporary key K = SHA256(t + ID). Using this temporary key, a symmetric encryption algorithm, such as the AES algorithm, is used to encrypt the sharded data packet to ensure the security of the data during the transmission process.

[0095] Set up an encrypted relay node: Specify at least one encrypted relay node in the dynamic routing path. For example, select a security gateway located at the boundary between the bank's internal network and the external network as the encrypted relay node. This node is responsible for the distribution and update of temporary keys. Before data transmission, the encrypted relay node securely distributes the generated temporary keys to the sender and the receiver. As data transmission progresses, to improve security, the temporary keys are updated regularly, and new temporary keys are recalculated and distributed, such as every 10 minutes, to ensure the encryption security of the data throughout the transmission process and prevent sensitive data from being stolen or tampered with.

[0096] Example 5:

[0097] This embodiment comprehensively considers the computing resources and storage resources of edge nodes, as well as the number of protocol conversions and routing hops during data transmission. At the same time, it combines the energy consumption of terminal devices to optimize the data transmission strategy, improve resource utilization, reduce transmission costs, and ensure the efficient operation of the system.

[0098] Taking the intelligent security monitoring system as an example, it includes a large number of monitoring cameras as Internet of Things terminal devices, as well as multiple edge nodes and cloud servers. The specific steps for implementing resource optimization and transmission strategy adjustment in this system are as follows:

[0099] Edge node resource evaluation and video analysis routing: Real-time statistics of the computing resource utilization rate and remaining storage capacity of each edge node. Assume that the computing resource utilization rate of edge node 1 is 40%, and the remaining storage capacity is 50GB; the computing resource utilization rate of edge node 2 is 70%, and the remaining storage capacity is 20GB. When the target transmission protocol of the sharded data packet is the video stream protocol, a computing resource utilization rate threshold is preset, such as 50%. If the computing resource utilization rate of edge node 1 is lower than this threshold, then route the video stream sharded data packet to edge node 1 for real-time video analysis, and use its idle computing resources for operations such as target detection and behavior analysis to reduce the data transmission pressure and the computing burden on the cloud server. If the computing resource utilization rate of an edge node is higher than the threshold, such as edge node 2, then route the sharded data packet to the cloud server to ensure that the video analysis task can be completed smoothly.

[0100] Fragmented Packet Aggregation and Protocol Switching: During data transmission, the number of protocol conversions and routing hops of the collected fragmented packets are counted. The preset threshold for the number of protocol conversions is 3 times, and the threshold for routing hops is 5 hops. If the number of protocol conversions of a fragmented packet of a video stream reaches 4 times during transmission, exceeding the preset number, or the routing hops reach 6 hops, exceeding the preset number, then the aggregation operation of the fragmented packets is triggered. Multiple fragmented packets are merged into an aggregated data block. For example, 10 fragmented packets are merged into one aggregated data block. At the same time, switch to a high-bandwidth transmission protocol, such as switching from the MQTT protocol to the TCP protocol, to improve transmission efficiency, reduce transmission latency, and reduce performance losses caused by frequent protocol conversions and excessive routing hops.

[0101] Energy Consumption Prediction and Low-Power Mode Switching: An energy consumption model is constructed for each monitoring camera by collecting data on the relationship between historical transmission power consumption and data volume for training. Suppose the energy consumption model formula obtained after training is P = c1D + c2, where P is the transmission power consumption, D is the data volume, and c1, c2 are model coefficients. According to the size D of the current fragmented packet current and the target transmission protocol, predict the transmission energy consumption P predict = c1D current + c2. A preset threshold for the remaining battery power of the terminal device is set, such as 20%. If the predicted energy consumption exceeds this threshold, for example, the predicted energy consumption will cause the remaining battery power of the device to be lower than 20%, then switch to the low-power transmission mode. The transmission frequency can be reduced, such as changing the data transmission from once per second to once every 5 seconds; or compression coding can be enabled, such as using the H.265 video coding standard to compress video data to reduce the data volume, thereby reducing the transmission energy consumption, extending the service life of the terminal device, and ensuring the continuous and stable operation of the intelligent security monitoring system.

[0102] It should be noted that in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "including", "comprising" or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent to such process, method, article or device.

[0103] Although the embodiments of the present invention have been shown and described, for those of ordinary skill in the art, it can be understood that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for transmitting data information of the Internet of Things, characterized in that: include: Acquire multi-source data streams of IoT terminal devices in real time, wherein the multi-source data streams include sensor data, video streams, and control instructions; Dynamically fragment multi-source data streams based on data stream types to generate fragmented data packets; The dynamic slicing includes: using fixed length slicing for sensor data, using inter-frame correlation based slicing for video streams, and using priority marking slicing for control instructions; According to a preset transmission protocol set, a target transmission protocol is matched for each fragmented data packet; the transmission protocol set includes: MQTT, CoAP and a custom low-latency protocol; Bind the fragmented data packets with the matching target transport protocol, and generate a dynamic routing path based on the priority tag of the fragmented data packets; the dynamic routing path is determined by calculating the delay sensitivity, link load rate and hop count constraint of the fragmented data packets; The fragmented data packets bound to the target transport protocol are transmitted along the dynamic routing path to the target edge node or cloud server.

2. The method for transmitting data information of the Internet of Things according to claim 1, characterized in that: Also includes: Real-time monitoring of network status parameters of each transmission link, including bandwidth utilization, packet loss rate and jitter value; Constructing a link quality assessment model, wherein the link quality assessment model is generated by training the relationship between historical network status parameters and transmission success rate; Input the current network status parameters into the link quality assessment model and output the dynamic weight value of each transmission link; The dynamic routing path of the fragmented data packet is adjusted according to the dynamic weight value, and the link with the weight value higher than the preset threshold is preferentially selected.

3. The method for transmitting data information of the Internet of Things according to claim 1, characterized in that: Also includes: When the target transmission protocol of the fragmented data packet is a custom low-latency protocol, the fragmented data packet is redundantly encoded to generate a redundant check block; Insert at least one backup node in the dynamic routing path and distribute the redundant check blocks to the backup node; If it is detected that the packet loss rate of the primary transmission path exceeds the preset threshold, the backup node is triggered to recover the lost fragmented data packets based on the redundant check blocks.

4. The method for transmitting data information of the Internet of Things according to claim 1, characterized in that: Also includes: During the transmission process, the transmission delay and integrity indicators of each fragmented data packet are counted in real time; If the transmission delay difference of the fragmented data packets of the same data stream exceeds the preset delay tolerance, the unreached fragmented data packets are reassembled in the local cache and a retransmission request is triggered; If the integrity index of the fragmented data packet is lower than the preset threshold, data repair is performed based on the redundant check block or historical fragmented data.

5. The method for transmitting data information of the Internet of Things according to claim 1, characterized in that: Also includes: Divide the security level of data flow according to the type of IoT terminal equipment and business scenarios; Dynamically encrypting the fragmented data packets whose security level is higher than a preset threshold, wherein the dynamic encryption includes: generating a temporary key based on a generation timestamp of the fragmented data packets and a unique device identifier; At least one encryption relay node is designated in the dynamic routing path to perform distribution and update of temporary keys.

6. The method for transmitting data information of the Internet of Things according to claim 1, characterized in that: Also includes: Statistics on computing resource utilization and remaining storage capacity of each edge node; If the target transmission protocol of the fragmented data packet is a video streaming protocol and the computing resource utilization of the edge node is lower than a preset threshold, the fragmented data packet is routed to the edge node for real-time video analysis; Otherwise, the fragmented data packet is routed to the cloud server.

7. The method for transmitting data information of the Internet of Things according to claim 1, characterized in that: Also includes: During the transmission process, the number of protocol conversions and routing hops of the fragmented data packets are collected; If the number of protocol conversions exceeds the preset number or the number of routing hops exceeds the preset number, the aggregation operation of the fragmented data packets is triggered, multiple fragmented data packets are merged into an aggregated data block, and switched to a high-bandwidth transmission protocol for transmission.

8. The method for transmitting data information of the Internet of Things according to claim 1, characterized in that: Also includes: Build an energy consumption model for each IoT terminal device, where the energy consumption model is generated by training the relationship between historical transmission power consumption and data volume; Predict the transmission energy consumption based on the size of the current fragmented data packet and the target transmission protocol; If the predicted energy consumption exceeds the remaining power threshold of the terminal device, it switches to a low-power transmission mode, which includes reducing the transmission frequency or enabling compression coding.

9. A switch, characterized in that: include: The data slicing module is used to dynamically slice the multi-source data streams based on the data stream type and generate sliced ​​data packets; A protocol matching module, used for matching a target transport protocol for a fragmented data packet according to a transport protocol set; A routing calculation module, used to generate a dynamic routing path based on the priority tag of the fragmented data packet and the network status parameters; A transmission execution module, used for transmitting the fragmented data packets bound to the target transmission protocol along the dynamic routing path; The redundant processing unit is used to generate redundant check blocks for the fragmented data packets of the custom low-latency protocol and manage backup nodes.

10. An Internet of Things data transmission system, characterized in that: include: A terminal device cluster, configured to generate a multi-source data stream and execute the method according to any one of claims 1 to 8; A network of edge nodes that receive fragmented packets and perform real-time analysis or forwarding; Cloud servers, used to store aggregated data blocks and provide global resource scheduling; Protocol conversion gateway, used for adaptive conversion and data format unification between different transmission protocols.

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