Real-time communication network construction method and system based on LoRa ad hoc network technology

Abstract

The invention discloses a real-time communication network construction method and system based on a LoRa ad hoc network technology, and the method comprises the steps: extracting business flow characteristics through a core layer gateway, carrying out the spatial clustering, and determining a cluster head node; the cluster head node broadcasts a clustering result; performing service flow classification, and determining access modes of different service flow classifications; calculating expected transmission times and node residual energy through a bidirectional link detection packet, and dynamically optimizing a multi-hop path; the cluster head node receives the link quality data reported by the terminal and dynamically adjusts a spreading factor; the cluster head node and the core layer gateway carry out key negotiation to generate a session key; the LoRa data packet is converted into a standard message through the core layer gateway; and the cluster head node compresses and gathers node data of the terminals in the cluster, and transmits the node data to the core layer gateway in a multi-hop mode. According to the scheme, the problems of fierce channel competition, routing stiffness and insufficient clock synchronization precision in the prior art can be solved, and the service requirements of high real-time performance and high reliability of a power system are met.

Description

Technical Field

[0001] The present invention relates to the field of communication technologies, and in particular to a method and system for constructing a real-time communication network based on LoRa self-organizing network technology. Background Art

[0002] With the widespread integration of distributed photovoltaic, energy storage, and electric vehicle charging stations into distribution networks, traditional centralized communication architectures are unable to achieve millisecond-level end-to-end communication and coordinated control of massive terminals in scenarios such as rapid fault isolation and dynamic power balancing. LoRa-based self-organizing networking technology, due to its long-range and low-power characteristics, has become a preferred solution. However, the existing LoRaWAN protocol suffers from fierce channel contention, rigid routing, and insufficient clock synchronization accuracy, making it difficult to meet the high-real-time and high-reliability business requirements of power systems. Summary of the Invention

[0003] In response to the above-mentioned defects, the present invention provides a method and system for constructing a real-time communication network based on LoRa self-organizing network technology, which solves the problems of fierce channel competition, rigid routing and insufficient clock synchronization accuracy in the existing technology, and meets the business requirements of high real-time performance and high reliability of the power system.

[0004] An embodiment of the present invention provides a method for constructing a real-time communication network based on LoRa self-organizing network technology, the method comprising: The core layer gateway receives the registration request sent by the terminal and extracts the service traffic characteristics; it performs spatial clustering based on the extracted characteristics to form local clusters and determine the cluster head node; The cluster head node broadcasts the clustering result to all nodes in the local cluster; classifies the service flow and determines the access mode of different service flow classifications; calculates the expected number of transmissions and the remaining energy of the node through a bidirectional link detection packet, and dynamically optimizes the multi-hop path based on the expected number of transmissions and the remaining energy of the node; The cluster head node receives the link quality data reported by the terminal, dynamically adjusts the spreading factor according to the link quality data, and updates the communication parameters of the cluster head node according to the adjusted spreading factor; The cluster head node and the core layer gateway perform key negotiation to generate a session key; and convert the LoRa data packet into a standard message through the core layer gateway; The cluster head node compresses and aggregates the node data of the terminals in the cluster, and transmits the data to the core layer gateway in a multi-hop manner.

[0005] Preferably, the registration request includes device ID, GPS coordinates and service type; The business flow characteristics include business flow density, business flow density ; is the number of data packets reported by the node in the time window, and T is the length of the sampling time window.

[0006] Preferably, performing spatial clustering based on the extracted features to form local clusters and determining cluster head nodes includes: The core layer gateway randomly selects the center point position by maximizing the spacing principle, and performs clustering based on the K-means clustering algorithm to assign different nodes to different local clusters; Calculate the comprehensive ability scores of different nodes in each local cluster, and select the node with the highest comprehensive ability score as the cluster head node.

[0007] Preferably, the clustering loss function of the K-means clustering algorithm is ; The comprehensive capability score of the i-th node ; in, is the loss value, k is the number of local clusters; is the feature vector of the jth node; represents the i-th local cluster; is the center point position of the i-th local cluster; is the remaining energy ratio of the i-th node, is the link quality indicator of the i-th node, is the computing capability index of the i-th node, α, β and γ are weighting coefficients.

[0008] Preferably, performing service flow classification and determining access methods for different service flow classifications include: Business flows are divided into real-time and non-real-time types according to their performance requirements. A fixed time slot access method is used for real-time service flows, and a competitive access method is used for non-real-time service flows.

[0009] Preferably, the dynamically optimizing the multi-hop path according to the expected number of transmissions and the remaining energy of the node includes: Calculating comprehensive path cost values ​​of different paths according to the expected number of transmissions and the remaining energy of the node; Select the path with the smallest comprehensive path cost as the optimal path; Among them, the comprehensive path cost value from the i-th node to the j-th node is ; and is the weight coefficient, and are the node residual energy ratios of the j-th node and the i-th node, is the expected number of successful transmissions on the path from the i-th node to the j-th node.

[0010] Preferably, the link quality data includes a current signal-to-noise ratio and a current packet loss rate; The dynamically adjusting the spreading factor according to the link quality data includes: When the current signal-to-noise ratio is greater than a preset first signal-to-noise ratio threshold, and the current packet loss rate is less than a preset first packet loss rate threshold, reducing the current spreading factor by a preset first amplitude; When the current signal-to-noise ratio is less than a preset second signal-to-noise ratio threshold, and the current packet loss rate is greater than a preset second packet loss rate threshold, increasing the current spreading factor by a preset second amplitude; The first signal-to-noise ratio threshold is greater than the second signal-to-noise ratio threshold, the first packet loss rate threshold is less than the second packet loss rate threshold, and the initial spreading factor is a preset value.

[0011] Preferably, the cluster head node and the core layer gateway perform key negotiation to generate a session key; and convert the LoRa data packet into a standard message through the core layer gateway, including: The cluster head node generates a node private key and a node public key, and sends the node public key to the core layer gateway; The core layer gateway generates a gateway private key and a gateway public key, and generates a shared key based on the node public key and the gateway public key; generates an AES key based on the shared key through a key derivation algorithm; encrypts each data block based on the AES key and a pre-generated random initial counter; and uses the encrypted ciphertext and the random initial counter as the standard message.

[0012] Preferably, the cluster head node compresses and aggregates the node data of the terminals in the cluster and transmits the data to the core layer gateway via a multi-hop manner, including: The cluster head node reports the complete initial data to the core layer gateway, and calculates the difference between the current data and the initial data in each subsequent cycle; when the difference is less than a preset threshold, the current data is uploaded to the core layer gateway; when the difference is not less than the threshold, the current data is uploaded to the core layer gateway; The core layer gateway detects the performance indicators of the cluster head nodes in real time, and sends network optimization instructions to the corresponding cluster when a performance anomaly is detected.

[0013] Another embodiment of the present invention provides a real-time communication network construction system based on LoRa self-organizing network technology, the system comprising: a core layer gateway and a cluster head node; The core layer gateway receives the registration request sent by the terminal, extracts the service traffic characteristics; performs spatial clustering based on the extracted characteristics to form a local cluster, and determines the cluster head node; The cluster head node broadcasts the clustering result to all nodes in the local cluster; classifies the service flow and determines the access mode of different service flow classifications; calculates the expected number of transmissions and the remaining energy of the node through a bidirectional link detection packet, and dynamically optimizes the multi-hop path based on the expected number of transmissions and the remaining energy of the node; The cluster head node receives the link quality data reported by the terminal, dynamically adjusts the spreading factor according to the link quality data, and updates the communication parameters of the cluster head node according to the adjusted spreading factor; The cluster head node and the core layer gateway perform key negotiation to generate a session key; and convert the LoRa data packet into a standard message through the core layer gateway; The cluster head node compresses and aggregates the node data of the terminals in the cluster, and transmits the data to the core layer gateway in a multi-hop manner.

[0014] The present invention provides a method and system for constructing a real-time communication network based on LoRa self-organizing network technology. The core layer gateway receives registration requests sent by terminals and extracts service traffic characteristics. Spatial clustering is performed based on the extracted characteristics to form local clusters and determine cluster head nodes. The cluster head node broadcasts the clustering results to all nodes in the local cluster. Service flows are classified to determine access methods for different service flow classifications. The expected number of transmissions and node residual energy are calculated using bidirectional link detection packets, and multi-hop paths are dynamically optimized based on the expected number of transmissions and node residual energy. The cluster head node receives link quality data reported by the terminals, dynamically adjusts the spreading factor based on the link quality data, and updates the communication parameters of the cluster head node based on the adjusted spreading factor. The cluster head node and the core layer gateway perform key negotiation to generate a session key. The core layer gateway converts LoRa data packets into standard messages. The cluster head node compresses and aggregates node data from terminals within the cluster and transmits it to the core layer gateway via multi-hop. This solution can solve the problems of fierce channel competition, rigid routing, and insufficient clock synchronization accuracy in the existing technology, meeting the high real-time and high reliability business requirements of the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 The present invention provides a flow chart of a method for constructing a real-time communication network based on LoRa self-organizing network technology. DETAILED DESCRIPTION

[0016] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0017] See also Figure 1 , is a flow chart of a method for constructing a real-time communication network based on LoRa self-organizing network technology provided by an embodiment of the present invention, the method comprising steps S1 to S5: Step S1: The core layer gateway receives the registration request sent by the terminal and extracts the service traffic characteristics; performs spatial clustering based on the extracted characteristics to form local clusters and determines the cluster head node; Step S2: The cluster head node broadcasts the clustering result to all nodes in the local cluster; classifies the service flow and determines the access mode of different service flow classifications; calculates the expected number of transmissions and the node residual energy through a bidirectional link detection packet, and dynamically optimizes the multi-hop path based on the expected number of transmissions and the node residual energy; Step S3, the cluster head node receives the link quality data reported by the terminal, dynamically adjusts the spreading factor according to the link quality data, and updates the communication parameters of the cluster head node according to the adjusted spreading factor; Step S4, the cluster head node and the core layer gateway perform key negotiation to generate a session key; and the core layer gateway converts the LoRa data packet into a standard message; Step S5: the cluster head node compresses and aggregates the node data of the terminals in the cluster, and transmits the data to the core layer gateway via a multi-hop manner.

[0018] During the specific implementation of this embodiment, terminal registration and feature collection are first performed. The terminal node sends a registration request (including device ID, GPS coordinates, and service type) to the core layer gateway. The gateway then uses the edge computing module to analyze the service traffic density (such as the number of times a photovoltaic inverter reports per second). Finally, the node's geographic location and service weight are stored as cluster feature parameters.

[0019] Dynamic clustering and cluster head election: The core layer gateway clusters nodes based on geography and service density using the K-means algorithm. Cluster heads are then elected based on a cluster head scoring model (weighted by residual energy, link quality, and computing power). The cluster head node then broadcasts the clustering results to all members of the cluster.

[0020] Perform hybrid access mechanism scheduling, with the cluster head node classifying service flows and determining access methods for different service flow categories; For example, services are divided into real-time (such as protection signals) and non-real-time (such as meter data). Fixed TDMA time slots (20ms per frame × 4) are allocated to the real-time class, and the non-real-time class uses CSMA / CA competitive access with a dynamic backoff window.

[0021] Dynamic routing optimization is performed, where the cluster head node calculates the expected number of transmissions and the node's remaining energy through a bidirectional link detection packet, then selects the optimal path based on a path cost formula, and triggers a traffic detour mechanism in the event of congestion.

[0022] Adaptive spreading factor adjustment is performed, and the terminal periodically reports link quality data including SNR (signal-to-noise ratio) and PLR (packet loss rate) to the cluster head node. The cluster head node dynamically switches the spreading factor according to the preset threshold and updates the LoRa communication parameters of all nodes in the network.

[0023] Encrypted transmission and protocol mapping are performed, the cluster head node and the core layer gateway perform key negotiation, generate a session key, and convert the LoRa data packet into an IEC 61850 MMS message through the core layer gateway.

[0024] Data aggregation and feedback: The cluster head node aggregates the cluster data (Delta encoding compression), and then transmits it to the core layer gateway through multi-hop routing. Finally, the core layer gateway feeds back the network status (such as congestion alarm) to the terminal node to trigger parameter adjustment.

[0025] This paper addresses the challenges of existing power distribution network communication systems, such as insufficient real-time performance, poor scalability, and weak protocol compatibility. By proposing a method for constructing a distributed resource real-time communication network based on LoRa self-organizing networks, this approach effectively improves the overall performance of the communication network in power distribution network scenarios through dynamic clustering, hybrid access scheduling, dynamic routing optimization, adaptive spread spectrum adjustment, full-link encryption, and standard protocol mapping. This method addresses the existing challenges of intense channel competition, rigid routing, and insufficient clock synchronization accuracy, meeting the high real-time and high reliability requirements of power systems.

[0026] In another embodiment of the present invention, during the implementation of step S2, upon system initialization or when a terminal node is newly connected to a LoRa network, the node must first complete a registration process. This registration process not only ensures terminal identity management but also extracts the node's geographic location information and service characteristics (traffic density) through edge computing, laying the data foundation for subsequent dynamic clustering.

[0027] The terminal node sends a registration request to the core layer gateway through the LoRa communication link. The registration request contains the following information: Device ID: used to uniquely identify the terminal node.

[0028] GPS coordinates (GPS): represent the geographical location of the node.

[0029] Business type (Type): such as photovoltaic monitoring, load monitoring, protection device, etc.

[0030] The gateway parses the request content and calls the edge computing module to extract business traffic features: Define the business flow density (FD) indicator. The larger the FD indicator, the higher the node data activity, and more resource guarantees are required. The calculation formula is as follows: ; in, is the number of data packets reported by node i within the time window; is the sampling time window length.

[0031] The node Recorded in the feature library for dynamic clustering.

[0032] In another embodiment provided by the present invention, when the above step S2 is implemented, specifically: Spatial clustering is performed based on node characteristic parameters to form a local cluster structure, and cluster head nodes are selected based on energy, link quality and computing power to optimize the network structure.

[0033] Clustering is performed based on the K-means clustering algorithm, and nodes are assigned to the nearest cluster center according to the clustering loss function; In each cluster, the comprehensive ability scores of different nodes in each local cluster are calculated based on node energy, link quality, and computing power, and the node with the highest comprehensive ability score is selected as the cluster head node.

[0034] In another embodiment of the present invention, the clustering loss function of the K-means clustering algorithm is: ; The comprehensive capability score of the i-th node ; in, is the loss value, k is the number of local clusters; is the feature vector of the jth node; represents the i-th local cluster; is the center point position of the i-th local cluster; is the remaining energy ratio of the i-th node, is the link quality indicator of the i-th node, is the computing capability index of the i-th node, α, β and γ are weighting coefficients.

[0035] Clustering is performed based on the K-means clustering algorithm. The goal is to minimize the differences between nodes in the cluster. The initial center point is randomly selected by maximizing the spacing principle. The algorithm avoids random selection of center points during initialization and adopts the probability distance principle: initially a random point is selected as the first cluster center, and then each time a point farther away from the existing cluster center is selected as the new cluster center to increase the stability of the clustering and minimize the initial cluster center selection bias, thereby improving the clustering effect.

[0036] In another embodiment of the present invention, the process of classifying the service flow is performed in step S2, specifically: Different access mechanisms are adopted according to different service types (real-time and non-real-time) to ensure the dual goals of low latency and high resource utilization.

[0037] Cluster head service flows are classified into real-time (such as fault trip protection, which requires extremely low latency) and non-real-time (such as power data, load records, which can accept a certain delay).

[0038] Two access mechanisms are used for different types of services. TDMA ensures collision-free transmission of critical data and is suitable for high-reliability scenarios. CSMA / CA utilizes channel idleness perception to improve overall resource utilization and is suitable for lightly loaded services. The specific service access mechanisms are as follows: For real-time services, TDMA access (fixed time slot mode) is used: The overall time is divided into frames, each frame is 80ms, and is further divided into four 20ms sub-time slots; the cluster head pre-assigns the time slot number corresponding to each node; the node only transmits within the designated time slot to avoid conflicts.

[0039] For non-real-time services, CSMA / CA access (contention access method) is adopted.

[0040] The node monitors whether the channel is idle; if it is idle, it randomly generates a backoff time B~U(0,CW) and seizes the channel after the countdown; after the transmission is completed, it releases the channel; in the event of a conflict, the window CW is dynamically increased.

[0041] The two access modes are scheduled in parallel within a cluster without interfering with each other, thus achieving traffic diversion management.

[0042] In another embodiment provided by the present invention, when dynamic path optimization is performed, specifically: Based on the link transmission success rate and node energy remaining, the multi-hop path is dynamically optimized to reduce energy consumption and improve the success rate.

[0043] Periodically exchange link detection packets and calculate the expected number of transmissions ETX. ETX represents the expected number of transmissions required for successful data transmission on a link. The smaller the ETX, the better the link, and the more likely it is to be selected. The expected number of transmissions for successful transmission on the path from the i-th node to the j-th node is ; in, is the success probability of single-hop transmission from the i-th node to the j-th node.

[0044] Record the remaining energy ratio of the node; The optimal path is selected based on the comprehensive path cost calculation formula. The calculation method is as follows: The path with the smallest comprehensive path cost is selected as the optimal path.

[0045] The comprehensive path cost from the i-th node to the j-th node is: .

[0046] in, , is the weight coefficient, and are the node residual energy ratios of the j-th node and the i-th node respectively.

[0047] In another embodiment of the present invention, when performing adaptive spreading factor adjustment, specifically: The link quality data includes a current signal-to-noise ratio and a current packet loss rate; Based on the real-time link quality (SNR, PLR), the LoRa terminal spreading factor (SF) is dynamically adjusted to adapt to changes in the communication environment.

[0048] The node periodically reports the current signal-to-noise ratio (SNR) and the current packet loss rate (PLR). The calculation method is as follows: ; ; in, is the received useful signal power, is the received background noise power; is the total number of packets sent by the node, The number of data packets successfully received by the gateway.

[0049] Dynamically adjust the LoRa terminal spreading factor SF based on the following judgment mechanism: When the current signal-to-noise ratio is greater than a preset first signal-to-noise ratio threshold, and the current packet loss rate is less than a preset first packet loss rate threshold, reducing the current spreading factor by a preset first amplitude; When the current signal-to-noise ratio is less than a preset second signal-to-noise ratio threshold, and the current packet loss rate is greater than a preset second packet loss rate threshold, increasing the current spreading factor by a preset second amplitude; For example, ; in, is the spreading factor currently used by the node, is the adjusted spreading factor, is the first signal-to-noise ratio threshold, is the second signal-to-noise ratio threshold, is the first packet loss rate threshold, is the second packet loss rate threshold. It is negotiated by the node based on the link quality when it first accesses.

[0050] It should be noted that, in this embodiment, 1 is used as the first amplitude and the second amplitude. In other embodiments, they can be set to other values.

[0051] Improve communication efficiency by periodically updating node spreading parameters.

[0052] In another embodiment of the present invention, when performing encrypted transmission and protocol mapping, specifically: To ensure the security of data transmission between nodes in the LoRa ad hoc network of the distribution network, the ECDH protocol is introduced for key negotiation, and the AES-128-CTR encryption mode is used for end-to-end data protection. Furthermore, the gateway encapsulates the encrypted data using standard protocols to support compatible access to the master station system.

[0053] ECDH (Elliptic Curve Diffie–Hellman) is a secure key agreement protocol based on elliptic curve cryptography (ECC). In specific applications: On the node side, a pair of keys is generated for each node, including the node private key and the node public key , and the node public key Sent to the gateway.

[0054] On the gateway side, the gateway also generates its own gateway private key and the gateway public key ;After receiving the node public key, calculate the shared key , the calculation formula is as follows: ; AES (Advanced Encryption Standard) is a widely used symmetric encryption algorithm. AES-128-CTR (Counter Mode) is a stream cipher mode suitable for fast encryption of continuously transmitted data. The encryption process is as follows: Generate the session key using the ECDH negotiated in the previous step , generate AES keys through key derivation algorithm .

[0055] Initialize the counter. The system generates a random initial counter Nonce for each session.

[0056] For each data block, the following formula is used for encryption: ; in, is the encrypted ciphertext block i, is the i-th block of plaintext data, Enter the AES encrypted counter value. It is a bitwise exclusive OR operation.

[0057] Send ciphertext And the initial Nonce, the receiver synchronously increments the counter to decrypt and restore the original text.

[0058] After the gateway receives the encrypted data, it uses the same The decrypted original data is encapsulated into IEC 61850 MMS protocol standard message according to the preset mapping rules; the standard message is uploaded to the power grid dispatching control system through a dedicated interface to achieve seamless integration.

[0059] In another embodiment provided by the present invention, when data aggregation and feedback are performed, specifically: To improve communication efficiency and reduce energy consumption, the cluster head node compresses and aggregates data from the cluster's terminal nodes and transmits it to the core gateway via multiple hops. Simultaneously, the core gateway feeds back network control instructions based on the overall network's operational status, enabling adaptive optimization and dynamic adjustment of the communication network.

[0060] Perform data aggregation and Delta coding compression to reduce the amount of redundant data, reduce the burden of wireless transmission, improve overall network energy efficiency, and extend the battery life of terminal nodes; support large-scale node access at the same time and improve system scalability.

[0061] The principle and process of Delta coding compression are as follows: Initial reporting of complete data , only the change amount is sent in each subsequent cycle - If the change is lower than the set threshold, only the difference is uploaded. If the change is abnormal or serious packet loss is detected, upload the complete data Resynchronize.

[0062] Conduct network status feedback and adaptive control to maintain the stability, reliability, and efficiency of communication networks in dynamic environments; and avoid network paralysis due to node energy exhaustion or link congestion.

[0063] The core layer gateway monitors node energy, channel status, latency, packet loss rate and other indicators in real time; when an anomaly is detected, it sends network optimization instructions to the corresponding cluster; The optimization instructions include: adjusting the packet sending frequency, dynamic rerouting, re-electing cluster heads, and changing the spreading factor.

[0064] Through the above processing, this solution obtains a hierarchical communication network based on LoRa wireless technology, which organizes nodes in clusters, performs multi-hop forwarding through cluster head nodes, and finally aggregates all terminal data to the core gateway.

[0065] In distribution network applications, this network can be understood as five layers: terminal nodes, head nodes, cluster head relay hops, core layer gateways, and the main network. Each layer has a dedicated role division: the terminal is responsible for collecting data, the cluster head is responsible for collection and relaying, and the gateway is responsible for accessing the main network.

[0066] Clustering by nodes: Nodes in each area are automatically divided into a cluster based on location and business density.

[0067] Cluster head management: A cluster head node is selected in each cluster to be responsible for communicating with other nodes in the cluster, managing data, and forwarding information.

[0068] Data compression upload: The node does not directly upload all the data as it is, but uses Delta encoding (only transmits the changes), and the cluster head then packages it.

[0069] Multi-hop relay: Cluster heads can relay and forward data to form a hopping transmission link. Even if the nodes are far away, they can still be uploaded through relays.

[0070] Real-time monitoring and adjustment: The gateway continuously monitors network conditions and automatically instructs each node to adjust packet sending frequency, switch routes, and even reselect cluster heads.

[0071] To verify the effectiveness of the proposed method, simulation tests were conducted based on the Network Simulator 3 platform. The experimental settings are shown in Tables 1 to 6: Table 1 Experimental settings After the simulation test, the experimental comparison results are as follows: Table 2 End-to-end delay comparison Table 3 Network throughput comparison Table 4 Node energy consumption comparison table Table 5 Packet loss rate comparison table Table 6 Data compression efficiency table Based on the above simulation tests, this solution has the following significant effects and advantages compared with traditional communication network methods: Traditional LoRaWAN or pure CSMA / CA access mechanisms typically experience end-to-end service latency exceeding 200ms due to intense channel contention when the number of nodes exceeds 1000, making it difficult to meet the 50ms control requirements of power distribution systems. This hybrid mechanism, using TDMA fixed-slot scheduling for real-time services and CSMA / CA competitive access for non-real-time services, reduces high-priority data transmission latency to less than 85ms (at a scale of 5000 nodes), meeting the real-time control requirements of the IEC 61850-7-420 standard.

[0072] Traditional static clustering solutions experience severe cluster head load imbalance and a network throughput drop of over 60% when the number of nodes exceeds 3,000. This invention introduces a dynamic clustering and cluster head election mechanism based on node location and traffic density. Combined with ETX and an energy-weighted dynamic routing optimization strategy, it supports dynamic access for networks exceeding 5,000 nodes, increasing overall network throughput by over 40%. Cluster head switching and route repair mechanisms ensure communication stability in large-scale dynamic environments.

[0073] Traditional LoRa networks typically use simple or no encryption, making them vulnerable to man-in-the-middle and replay attacks. This invention introduces an ECDH key agreement mechanism between nodes and gateways, combined with efficient AES-128-CTR stream encryption, to achieve end-to-end full-link encryption protection, effectively preventing data leakage, forgery, and tampering, meeting the distribution network's demand for high-security data communications.

[0074] Traditional AODV or static routing protocols are slow to recover when link quality fluctuates dramatically, easily forming loops or link crashes. This invention combines real-time SNR and PLR monitoring with adaptive spreading factor (SF) adjustment, along with dynamic optimal routing reconstruction and cluster head reselection mechanisms. This enables the network to rapidly adapt and maintain stable and reliable communications in complex environments, such as fluctuating link quality, declining node energy, and localized congestion.

[0075] Traditional transmission typically involves uploading complete data, leading to wireless link congestion and increased energy consumption. This invention introduces Delta coding compression, uploading only the data delta. Combined with multi-hop cluster head data aggregation, this significantly reduces link load (compression rates can reach 30%-70%). Furthermore, through an adaptive packet transmission frequency strategy, it effectively extends terminal node battery life by over 20%.

[0076] The embodiment of the present invention further provides a real-time communication network construction system based on LoRa self-organizing network technology, the system comprising: a core layer gateway and a cluster head node; The core layer gateway receives the registration request sent by the terminal, extracts the service traffic characteristics; performs spatial clustering based on the extracted characteristics to form a local cluster, and determines the cluster head node; The cluster head node broadcasts the clustering result to all nodes in the local cluster; classifies the service flow and determines the access mode of different service flow classifications; calculates the expected number of transmissions and the remaining energy of the node through a bidirectional link detection packet, and dynamically optimizes the multi-hop path based on the expected number of transmissions and the remaining energy of the node; The cluster head node receives the link quality data reported by the terminal, dynamically adjusts the spreading factor according to the link quality data, and updates the communication parameters of the cluster head node according to the adjusted spreading factor; The cluster head node and the core layer gateway perform key negotiation to generate a session key; and convert the LoRa data packet into a standard message through the core layer gateway; The cluster head node compresses and aggregates the node data of the terminals in the cluster, and transmits the data to the core layer gateway in a multi-hop manner.

[0077] It should be noted that the real-time communication network construction system based on LoRa self-organizing network technology provided in the embodiment of the present invention can execute the real-time communication network construction method based on LoRa self-organizing network technology described in any of the above embodiments. The specific functions of the real-time communication network construction system based on LoRa self-organizing network technology are not described here.

[0078] The above is a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A method for constructing a real-time communication network based on LoRa self-organizing network technology, characterized in that: The method comprises: The core layer gateway receives the registration request sent by the terminal and extracts the service traffic characteristics; it performs spatial clustering based on the extracted characteristics to form local clusters and determine the cluster head node; The cluster head node broadcasts the clustering result to all nodes in the local cluster; classifies the service flow and determines the access mode of different service flow classifications; calculates the expected number of transmissions and the remaining energy of the node through a bidirectional link detection packet, and dynamically optimizes the multi-hop path based on the expected number of transmissions and the remaining energy of the node; The cluster head node receives the link quality data reported by the terminal, dynamically adjusts the spreading factor according to the link quality data, and updates the communication parameters of the cluster head node according to the adjusted spreading factor; The cluster head node and the core layer gateway perform key negotiation to generate a session key; and convert the LoRa data packet into a standard message through the core layer gateway; The cluster head node compresses and aggregates the node data of the terminals in the cluster, and transmits the data to the core layer gateway in a multi-hop manner.

2. The method for constructing a real-time communication network based on LoRa self-organizing network technology as claimed in claim 1, wherein: The registration request includes device ID, GPS coordinates and service type; The business flow characteristics include business flow density, business flow density ; is the number of data packets reported by the node in the time window, and T is the length of the sampling time window.

3. The method for constructing a real-time communication network based on LoRa self-organizing network technology as claimed in claim 1, wherein: The spatial clustering is performed based on the extracted features to form local clusters and determine cluster head nodes, including: The core layer gateway randomly selects the center point position by maximizing the spacing principle, and performs clustering based on the K-means clustering algorithm to assign different nodes to different local clusters; Calculate the comprehensive ability scores of different nodes in each local cluster, and select the node with the highest comprehensive ability score as the cluster head node.

4. The method for constructing a real-time communication network based on LoRa self-organizing network technology as claimed in claim 3, wherein: The clustering loss function of the K-means clustering algorithm is ; The comprehensive capability score of the i-th node ; in, is the loss value, k is the number of local clusters; is the feature vector of the jth node; represents the i-th local cluster; is the center point position of the i-th local cluster; is the remaining energy ratio of the i-th node, is the link quality indicator of the i-th node, is the computing capability index of the i-th node, α, β and γ are weighting coefficients.

5. The method for constructing a real-time communication network based on LoRa self-organizing network technology as claimed in claim 2, wherein: Classify service flows and determine access methods for different service flow categories, including: Business flows are divided into real-time and non-real-time types according to their performance requirements. A fixed time slot access method is used for real-time service flows, and a competitive access method is used for non-real-time service flows.

6. The method for constructing a real-time communication network based on LoRa self-organizing network technology as claimed in claim 1, wherein: The dynamically optimizing the multi-hop path according to the expected number of transmissions and the remaining energy of the node includes: Calculating comprehensive path cost values ​​of different paths according to the expected number of transmissions and the remaining energy of the node; Select the path with the smallest comprehensive path cost as the optimal path; Among them, the comprehensive path cost value from the i-th node to the j-th node is ; and is the weight coefficient, and are the node residual energy ratios of the j-th node and the i-th node, is the expected number of successful transmissions on the path from the i-th node to the j-th node.

7. The method for constructing a real-time communication network based on LoRa self-organizing network technology as claimed in claim 1, wherein: The link quality data includes a current signal-to-noise ratio and a current packet loss rate; The dynamically adjusting the spreading factor according to the link quality data includes: When the current signal-to-noise ratio is greater than a preset first signal-to-noise ratio threshold, and the current packet loss rate is less than a preset first packet loss rate threshold, reducing the current spreading factor by a preset first amplitude; When the current signal-to-noise ratio is less than a preset second signal-to-noise ratio threshold, and the current packet loss rate is greater than a preset second packet loss rate threshold, increasing the current spreading factor by a preset second amplitude; The first signal-to-noise ratio threshold is greater than the second signal-to-noise ratio threshold, the first packet loss rate threshold is less than the second packet loss rate threshold, and the initial spreading factor is a preset value.

8. The method for constructing a real-time communication network based on LoRa self-organizing network technology as claimed in claim 1, wherein: The cluster head node and the core layer gateway perform key negotiation to generate a session key; The core layer gateway converts the LoRa data packet into a standard message, including: The cluster head node generates a node private key and a node public key, and sends the node public key to the core layer gateway; The core layer gateway generates a gateway private key and a gateway public key, and generates a shared key based on the node public key and the gateway public key; generates an AES key based on the shared key through a key derivation algorithm; encrypts each data block based on the AES key and a pre-generated random initial counter; and uses the encrypted ciphertext and the random initial counter as the standard message.

9. The method for constructing a real-time communication network based on LoRa self-organizing network technology according to claim 1, wherein: The cluster head node compresses and aggregates the node data of the terminals in the cluster and transmits the data to the core layer gateway via a multi-hop method, including: The cluster head node reports the complete initial data to the core layer gateway, and calculates the difference between the current data and the initial data in each subsequent cycle; when the difference is less than a preset threshold, the current data is uploaded to the core layer gateway; when the difference is not less than the threshold, the current data is uploaded to the core layer gateway; The core layer gateway detects the performance indicators of the cluster head nodes in real time, and sends network optimization instructions to the corresponding cluster when a performance anomaly is detected.

10. A real-time communication network construction system based on LoRa self-organizing network technology, characterized in that: The system includes: a core layer gateway and a cluster head node; The core layer gateway receives the registration request sent by the terminal, extracts the service traffic characteristics; performs spatial clustering based on the extracted characteristics to form a local cluster, and determines the cluster head node; The cluster head node broadcasts the clustering result to all nodes in the local cluster; classifies the service flow and determines the access mode of different service flow classifications; calculates the expected number of transmissions and the remaining energy of the node through a bidirectional link detection packet, and dynamically optimizes the multi-hop path based on the expected number of transmissions and the remaining energy of the node; The cluster head node receives the link quality data reported by the terminal, dynamically adjusts the spreading factor according to the link quality data, and updates the communication parameters of the cluster head node according to the adjusted spreading factor; The cluster head node and the core layer gateway perform key negotiation to generate a session key; and convert the LoRa data packet into a standard message through the core layer gateway; The cluster head node compresses and aggregates the node data of the terminals in the cluster, and transmits the data to the core layer gateway in a multi-hop manner.

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