A node control method under a wireless network cluster

Abstract

The application discloses a node control method under a wireless network cluster and relates to the field of wireless network cluster control.The method comprises the following steps: a central distributed wireless network cluster model comprising a central service node, a policy control node and an edge node is established; the central service node generates node overview state information in response to receiving local state information transmitted by the edge node in the corresponding task area; the policy control node establishes a connection with the edge node to obtain detailed state information in response to receiving the node overview state information from the central service node; the policy control node determines policy decision information according to the detailed state information and performs policy distribution to the edge node and / or the policy control node in the corresponding area; when there are multiple task areas, the corresponding central service nodes of different task areas perform data synchronization based on a distributed data synchronization mechanism.Compared with the prior art, the application has good real-time performance, weak scene dependence and strong universality.

Description

Technical Field

[0001] The present invention relates to the technical field of wireless network cluster control, and more particularly to a node control method in a wireless network cluster. Background Art

[0002] Wireless network clusters have been widely used in various fields, such as drone swarms, sensor swarms, and mobile device swarms. Wireless network nodes in a cluster communicate and collaborate through networking, which is the foundation of many mission-based systems. However, due to energy and load constraints, wireless network nodes typically perform tasks within a specific area. The status information of each node requires centralized management and intelligent distribution, relying on an intelligent command system at the regional center. If scale is required, a distributed control solution with cascaded sites is necessary.

[0003] For large-scale wireless networks, distributed control solutions offer improved scalability but also face real-time challenges and complex system design. In distributed server-based control systems, while edge nodes can perform independent computations, communication barriers and environmental decision-making planning challenges persist. In large-scale operational or mission areas, communication barriers can lead to poor information transfer between nodes, impacting the system's overall collaborative capabilities. Effective environmental decision-making planning in multi-site deployments remains an unresolved issue, with existing research focusing on local optimization and lacking a comprehensive approach.

[0004] Furthermore, existing control algorithms (such as A* and genetic algorithms) suffer from strong scenario dependence and insufficient comprehensive optimization. First, they are often designed for specific scenarios and specific problems, lacking versatility and adaptability, and are unable to adapt well to changing environments and complex task requirements. Second, existing research has largely focused on optimizing a single function, lacking a comprehensive global optimization approach that considers multiple factors. This makes them incapable of handling complex multi-task and multi-strategy combinations. Summary of the Invention

[0005] In order to overcome at least one of the defects of the above-mentioned prior art, namely, poor real-time performance, strong scene dependence, poor versatility, and insufficient comprehensive optimization, the present invention provides a node control method in a wireless network cluster.

[0006] In order to solve the above technical problems, the technical solutions of the present invention are as follows:

[0007] In a first aspect, a node control method in a wireless network cluster includes:

[0008] Establishing a central distributed wireless network cluster model; wherein the central distributed wireless network cluster model is divided into one or more task areas, wherein one or more policy control nodes, one or more edge nodes, and a central service node are distributed within the task area, and the nodes in the task area communicate with each other based on a self-organizing network strategy;

[0009] The central service node generates node overview status information in response to receiving local status information transmitted by the one or more edge nodes in the corresponding task area;

[0010] In response to receiving the node overview status information from the central service node of the corresponding task area, the one or more policy control nodes establish connections with the one or more edge nodes to obtain detailed status information about the edge nodes;

[0011] The one or more policy control nodes determine policy decision information according to the detailed status information, and distribute the policy to the one or more edge nodes and / or the one or more policy control nodes in the corresponding area;

[0012] When there are multiple task areas, the corresponding central service nodes of different task areas perform data synchronization based on a distributed data synchronization mechanism.

[0013] In a second aspect, a computer program product comprises a computer program or computer executable instructions, wherein when the computer program or computer executable instructions are executed by a processor, the method of the first aspect is implemented.

[0014] Compared with the prior art, the beneficial effects of the technical solution of the present invention are:

[0015] The present invention discloses a node control method under a wireless network cluster for a central distributed wireless network cluster model, involving a central service node, a policy control node and an edge node in a task area. By adopting a self-organizing network strategy, network collisions are reduced and real-time problems are solved. Strategy determination is completed based on information exchange among the central service node, the policy control node and the edge nodes, and the method has weak scenario dependence and strong versatility. A distributed data synchronization mechanism is adopted to synchronize node and policy information to multiple central service nodes, thereby ensuring efficient task execution and data consistency in a distributed environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 The process of a node control method in a wireless network cluster in Example 1 of the present application is intended;

[0017] Figure 2 This is a schematic diagram of the structure of the central distributed wireless network cluster model in Example 1 of this application;

[0018] Figure 3 This is a schematic diagram of the self-organizing network structure in Example 1 of the present application;

[0019] Figure 4 This is a schematic diagram of the self-organizing network strategy flow in Example 1 of this application;

[0020] Figure 5 This is a schematic diagram of the information flow of the strategy generation process in Example 1 of the present application;

[0021] Figure 6 Schematic diagram of the real-time data collection mechanism in Example 1 of the present application;

[0022] Figure 7 This is a schematic diagram of the workflow of the strategy integration real-time interactive system in Example 1 of this application. DETAILED DESCRIPTION

[0023] The terms "first", "second" etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequential order. It should be understood that the terms used in this way can be interchangeable in appropriate circumstances, and this is merely a way of distinguishing the objects of the same attribute when describing them in the embodiments of the present application. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, so that the process, method, system, product or equipment comprising a series of units need not be limited to those units, but may include other units that are not clearly listed or inherent to these processes, methods, products or equipment. The term "determine" widely covers various actions, may include obtaining, calculating, computing, processing, deriving, investigating, searching (for example, searching in a table, a database or other data structure), ascertaining and similar actions, may also include receiving (for example, receiving information), accessing (for example, accessing data in a memory) and similar actions, may also include generating, creating, establishing and similar actions, and parsing, selecting, selecting and similar actions etc. The relevant definitions of other terms will be provided in the following description.

[0024] It should be noted that when an element is considered to be "connected" to another element, it can be directly connected to the other element or connected to the other element through an intervening element. In addition, the "connection" in the following embodiments should be understood as "electrical connection", "communication connection", etc., if there is transmission of electrical signals or data between the connected objects.

[0025] The accompanying drawings are for illustrative purposes only and are not to be construed as limiting this patent;

[0026] In order to better illustrate this embodiment, some parts in the drawings may be omitted, enlarged, or reduced, and do not represent the actual product size;

[0027] It is understandable to those skilled in the art that some well-known structures and descriptions thereof may be omitted in the drawings.

[0028] The technical solution of the present invention is further described below with reference to the accompanying drawings and embodiments.

[0029] Example 1

[0030] This embodiment provides a node control method in a wireless network cluster. Figure 1 ,include:

[0031] S10, see Figure 2 , establish a central distributed wireless network cluster model; wherein, the central distributed wireless network cluster model is divided into one or more task areas, and one or more policy control nodes, one or more edge nodes and a central service node (i.e., regional center server) are distributed in the task area. The nodes in the task area communicate based on self-organizing network strategies to reduce network collisions and improve communication efficiency.

[0032] Specifically, one or more policy control nodes (also referred to as control nodes in this application) are represented by a set C={c1, c2, ..., c n}; Multiple wireless network edge nodes, the set is represented by E = {e1, e2, ..., e n A mobile central server is represented by S. In some non-limiting examples, the deployment of the mission area is represented by a triple R = {C, E, S}.

[0033] S20: The central service node generates node overview status information in response to receiving local status information transmitted by the one or more edge nodes in the corresponding task area.

[0034] S30: In response to receiving the node overview status information from the central service node of the corresponding task area, the one or more policy control nodes establish connections with the one or more edge nodes to obtain detailed status information about the edge nodes.

[0035] S40: The one or more policy control nodes determine policy decision information according to the detailed status information, and issue the policy to the one or more edge nodes and / or the one or more policy control nodes in the corresponding area.

[0036] S50: When there are multiple task areas, the corresponding central service nodes of different task areas perform data synchronization based on a distributed data synchronization mechanism.

[0037] It should be noted that this embodiment utilizes a self-organizing network strategy to optimize communication solutions, reduce network collisions, and improve communication efficiency. Through information exchange between the policy control node and the central service node, data from various edge nodes is integrated to generate policy decision information adapted to network conditions. The central service node is responsible for executing the policy individually or distributing it. This process ensures real-time and targeted policy generation, enabling the entire system to rapidly respond to changes in network conditions.

[0038] Furthermore, to ensure data consistency and task execution efficiency in a multi-region, multi-point wireless network environment, this embodiment introduces a distributed data synchronization mechanism to ensure data consistency across different regions and multiple central service nodes. Through this effective data synchronization mechanism, the present invention achieves efficient task allocation and data consistency in a distributed environment, enhancing the reliability and coordination of the system in large-scale networks.

[0039] It should be understood that each node in the task area includes the edge node, policy control node and central service node, and each of the edge node, policy control node and central service node is deployed with a communication module for implementing data transmission and policy update. The information exchange process can be expressed as:

[0040] In some specific implementations, the policy control nodes and edge nodes within the same mission area communicate wirelessly (including but not limited to Bluetooth, Wi-Fi, cellular networks, and SparkLink), the central service nodes and edge nodes communicate wirelessly, and the central service nodes and policy control nodes communicate wired (including but not limited to optical fiber and Ethernet). Different central service nodes in different mission areas communicate over long distances between regions using high-frequency wireless methods (including but not limited to HF, VHF, UHF, SHF, etc.). The connection between the edge node and the central service node can be a point-to-point wireless connection, or an indirect connection established through a relay node in the wireless network.

[0041] More specifically, in urban scenarios, the UHF band is preferred for wireless communications between different central service nodes in different mission areas. It should be understood that the UHF band has good penetration and a longer communication range, making it suitable for applications that require penetrating obstacles (such as buildings) or long-distance communication.

[0042] It should be noted that the communication between nodes n in the region adopts a self-organizing network strategy to ensure the stability of network traffic during the networking process. The self-organizing network communication system realizes the automatic configuration of nodes, route discovery, data transmission and node failure recovery. Figure 3As shown, each node not only acts as a data terminal but also as part of the network routing, ensuring the network's self-organization and self-healing capabilities. This design enables the network to adapt to dynamically changing network environments and provide reliable communication services.

[0043] As a non-limiting example, the policy control node utilizes storage resources and computing resources of the central service node directly connected thereto to determine the policy decision information.

[0044] In some preferred embodiments, see Figure 4 , the self-organizing network strategy includes:

[0045] At least one node in the central distributed wireless network cluster model acts as a coordination node, broadcasts networking notifications and configures network parameters to initialize the network;

[0046] Respond to the JoinRequest broadcast by the node not in the network i =(ID i , JoinMessage), at least one node that has joined the network authenticates the node that has not joined the network according to the network joining request, and returns the authentication response message JoinResponse after the authentication is successful i =Authenticate(ID i ,SecurityKey); where ID i Represents the unique identifier of the node, JoinMessage represents the message content of the join request; Authenticate(·) represents the authentication process; SecurityKey represents the security key;

[0047] In response to the node not connected to the network broadcasting the identity authentication response message to the network, the remaining nodes that have connected to the network decrypt or verify the identity authentication response message, determine that the information in the identity authentication response message is valid and meets expectations, accept the node not connected to the network to join the network, and update the routing table.

[0048] As a non-limiting example, the network parameters may be set as NetworkParameters={Channel, SSID, SecurityKey}; wherein Channel is the communication channel, SSID is the network name, and SecurityKey is the network security key.

[0049] Specifically, the process of authenticating the identity of a new node applying to join the network can be:

[0050] (1) The node to be added to the network signs its identity information with its private key. Other nodes can verify the signature using the public key to confirm the authenticity and integrity of the identity information.

[0051] (2) Once the identity information is confirmed, other nodes respond to the new node's authentication response message, and the new node generates the authentication response message JoinResponse i Broadcast to the network;

[0052] (3) After receiving the response message, other nodes in the network will use the same security key or public key to decrypt or verify the message. If the information in the response message is valid and meets expectations, the new node is accepted into the network.

[0053] To optimize transmission and load balancing, modern TCP / IP-based data transmission requires Layer 3 routing. In wireless networks, TCP / IP routing mechanisms are necessary to enable nodes to dynamically adapt to topology, implement multi-hop transmission, and ensure data transmission confirmation and retransmission.

[0054] In some optional embodiments, the self-organizing network strategy further includes:

[0055] In response to receiving a first route request message RouteRequest regularly broadcast by at least one node that has entered the network i =(SourceID i ,DestinationID i ,RequestID i ), at least one of the remaining nodes that have joined the network checks its routing table and returns a first routing response message RouteReply if it determines that the target node exists j ={DestinationID,SourceID i ,RoutePath); where SourceID i Indicates the source node identifier, DestinationID i Indicates the target node identifier, Request i Indicates the unique identifier of the request, and RoutePath indicates the path information from the source node to the target node;

[0056] In response to receiving the first routing response message, the node that initiated the first routing request updates a routing table to maintain a network topology.

[0057] It should be understood that nodes maintain the network topology by periodically exchanging routing update messages to ensure the accuracy of the routing table: TopologyUpdate i =Update(RouteTable i ), where Update(.) represents the update process of the routing table.

[0058] Furthermore, the self-organizing network strategy also includes:

[0059] The source node generates a data packet and encapsulates it into a data packet suitable for Mesh network transmission. i =(SourceID i ,Destination i ,Payload), determines the forwarding path of the data packet according to the routing table, and forwards the data packet to the next node Forward i→j =(DataPacket i ,NextHop j ); Payload represents data load, NextHop j The identifier of the next hop node;

[0060] When the data packet arrives at the target node, the target node unpacks the data packet and processes the data payload ReceivedData j =Proccess(Payload); wherein Process(·) represents the business processing process corresponding to the data payload.

[0061] Furthermore, the self-organizing network strategy also includes:

[0062] At least one node in the network detects a node failure through neighbor detection or link status monitoring and updates the routing table to reflect the change NodeFailure i =Detect(FailedNode); where NodeFailure i Indicates the failed node information detected by node i;

[0063] When a node failure is found in the network, other nodes in the network restore the network connection by recalculating the route RouteRebuild i =Recaculate(DailedNode) where Recaculate(.) represents the route reconstruction process. The at least one node that has joined the network broadcasts a second route request message to the network. Each node that receives the second route request message records the path information and forwards the second route request message. The target node or a relay node with a valid path returns a second route response, providing the new path information. After receiving the second route response, the source node updates its routing table and resumes data transmission via the new path, ensuring that the communication connection can be promptly restored in the event of network environment changes or node failure.

[0064] When the originally failed node recovers and rejoins the network, it broadcasts a rejoin message RejoinMessages in the network to notify the remaining nodes in the network and request to update the network topology. In response to receiving the rejoin message, the remaining nodes in the network update the routing table; wherein, the rejoin message includes the unique identifier ID corresponding to the originally failed node i In this way, the network can promptly integrate and recover nodes, ensuring the update of network topology and the continuity of communication.

[0065] In some preferred embodiments, see Figure 5 The central service node generates node overview status information in response to receiving local status information transmitted by one or more edge nodes in the corresponding task area, including:

[0066] The one or more edge nodes continuously monitor their own operating status to generate current status information, and package their own unique identification code and current status information into a local status information InfoPacket i =(ID i ,State i ); where ID i The unique identification code ID of the edge node i i , State i Indicates the current status information;

[0067] Specifically, the current status information includes but is not limited to communication protocol, communication frequency, node distance, CPU usage, memory occupancy, network connection status, battery power, etc.

[0068] After the one or more edge nodes establish a connection with the central service node of the corresponding task area through a wireless network, the packaged local state information is sent to the central service node. The process is as follows: Wherein, Send(·) indicates sending the local state information to the central service node S k ;

[0069] Specifically, the edge node may send the packaged information to the central service node through a point-to-point connection or through a relay node in the network.

[0070] The central service node receives the local state information from the one or more edge nodes, performs hash storage, and generates a state table. It also dynamically assigns a temporary ID to the corresponding edge node according to the unique identification code, and generates the node overview state information, waiting for continuous query;

[0071] Specifically, if the information packet from the edge node is encrypted, the central service node first decrypts the data using the corresponding key to restore the original information. The decrypted data is then verified for integrity and authenticity. This verification process ensures that the data has not been tampered with and comes from a trusted source. The central service node stores the verified valid information packet in a database or status table. The status data and unique identification code of each edge node are associated in the database for subsequent query and management. The central service node updates the dynamic status table based on the information transmitted by the node. This status table records the current status of all nodes in the network for real-time tracking and management. Based on the unique identification code of each edge node, the central service node assigns a temporary ID to each edge node. This temporary ID is used for subsequent communication and processing to ensure that nodes within the system can exchange data and operate securely.

[0072] In some optional embodiments, the one or more policy control nodes, in response to receiving the node overview status information from the central service node of the corresponding task area, establish a connection with the edge node to obtain detailed status information about the edge node, including:

[0073] The policy control node requests the central service node to obtain the node overview information, determines the target edge node to be connected to based on the node overview information, and transmits the corresponding coding information of the temporary ID of the target edge node to the central service node;

[0074] After decoding, the central server uses the state table to determine the real IP address of the target edge node, communicates with the target edge node based on the real IP address for authentication, and encrypts the real IP address and returns it to the policy control node after successful authentication;

[0075] After verifying the fingerprint information, the policy control node decrypts the real IP address and sends a connection request to the target edge node based on the real IP address to obtain at least partial control rights of the target edge node and the detailed status information.

[0076] It should be understood that in a single task area, the policy control node C k , Central service node S k and edge nodes E k The encryption authentication between the three is to prevent network intrusion, network interception, and network attacks. The local area control authority mechanism based on IP addresses can be further abstracted into an ID encryption mechanism, in which each network node generates a unique identifier (ID) based on its IP address. Formally, the node ID is expressed as:

[0077]

[0078] in, Indicates that the corresponding IP address IP i The encryption process of converting to a unique ID ensures the uniqueness and security of each node in the local area.

[0079] In some preferred embodiments, the determining of the policy decision information includes:

[0080] According to the task requirements of the overall control task (including but not limited to distributing tasks through control nodes, adjusting resource allocation, or executing path planning), the central service node selects at least one control strategy from the preset strategy library in combination with the environmental parameter information for evaluation and determines the optimal control strategy Decision. The selection process is expressed as:

[0081]

[0082] Where, Evaluate represents the evaluation function, which is used to evaluate the adaptability and effectiveness of the control strategy; Enviornment represents the environmental parameter information; s i ∈S represents the i-th control strategy, S represents the set of control strategies preset in the strategy library; Task represents the overall control task;

[0083] For all the policy control nodes in the task area k, the corresponding optimal control strategy is expressed as:

[0084] Decision k =argmaxEvaluate(s ik ,Task k ,E k )

[0085] Where s ik represents the i-th control strategy applicable to task area k, E k Indicates the environmental parameter information corresponding to the task area k;

[0086] One or more of the policy control nodes in the task area k perform task allocation based on the optimal control strategy and the detailed status information of the one or more edge nodes to determine the policy decision information T kj , the process is expressed as:

[0087] T kj =Assign(Node j ,Task k )

[0088] In the formula, Assign(·) represents the control task assignment process; Task k Indicates the control task corresponding to task area k; Node j represents the jth policy control node.

[0089] It should be understood that the overall control task The decision-making process is a comprehensive dynamic behavioral process based on the overall situation in the mission area.

[0090] For the convenience of understanding by those skilled in the art, Figure 5 The information flow during the strategy generation process in this embodiment is roughly as follows:

[0091] (1) Each edge node has a fixed unique identification code. The edge node transmits node information to the central service node through the wireless network, including the identification code and other current operating status information.

[0092] (2) The central service node of the corresponding task area performs hash storage and establishes a state table to dynamically assign temporary IDs to edge nodes. The assigned temporary IDs are stored in the server and wait for connection queries.

[0093] (3) Policy control node request status and obtain node overview status information.

[0094] (4) The policy control node transmits the corresponding edge node identification code to the central service node of the corresponding task area. After decoding, the central service node queries the corresponding ID in the status table, obtains the real node IP address, communicates with the edge node for authentication, and returns the IP result to the policy control node after success.

[0095] (5) After verifying the fingerprint information, the policy control node decrypts the IP address and sends the corresponding connection request to the single edge node. After the connection, it directly obtains partial control rights and more detailed information of the relevant edge node, implements individual policy control, and realizes refined operations.

[0096] (6) The central service node obtains policy decision information from the policy control node.

[0097] As a non-limiting example, the environmental parameter information can be node overview status information (generally speaking, node overview status information only accounts for a very small part of the environmental parameter information stored in the environmental parameter library), or it can be multimodal information transmitted by edge nodes, including but not limited to video data (such as video data collected from surveillance cameras, drones or other visual sensors), Ai-processed information (such as analyzing video data and identifying target object information in the video, such as pedestrians, vehicles or other objects of interest), GPS information (collecting and recording the location data of each node, including the node's location, movement trajectory and geographical area, etc.), mobile information (such as the drone's flight altitude, speed, heading and flight path, etc.), etc.

[0098] It should be understood that the primary purpose of the environmental parameter information in the environmental parameter library is to provide the necessary decision-making information for the policy generation and decision-making modules. This includes information such as hyperparameters that can be collected by sensors, derived through computational deduction, and manually input. This information does not necessarily need to be provided to users such as the policy control node in every decision. Some in-depth information (such as the historical estimated cost of moving the current node to a predetermined destination) is not required by users.

[0099] In some specific implementations, the environmental parameter information is stored in real time in an environmental parameter library by category for easy access. Each data type can be stored in a different set of data tables. Furthermore, the cache layer alleviates the pressure of database updates. The cache layer uses memory as a cache medium. Memory cache provides very fast data access. When using multiple regional central servers, the distributed system cache mechanism is used to disperse data across multiple nodes. Combined with efficient data sharding, load balancing, and replication mechanisms, it provides high-performance, highly available cache services.

[0100] like Figure 6 The figure shows a typical real-time data acquisition mechanism. Data from different sources is stored in different data areas depending on the data required. Data is received from various sensors or network interfaces through the data front-end API, which calls the operating system to manage communication hardware resources and enter the system. The front-end API receives data requests from various sources and passes the data to the message queue. The message queue is responsible for asynchronously processing the data flow, ensuring efficient and reliable data transmission. The data is passed from the message queue to the data cleaning and processing module for necessary cleaning and formatting. The processed data is ready for further analysis or storage. The data is first stored in the cache layer, which temporarily stores hot data to improve access speed. The data is then persisted in the database to ensure long-term data storage and management. The processed data is organized and stored according to different classification criteria, ensuring effective data management and fast access. The classified data can be archived or analyzed as needed.

[0101] It should be noted that the policy library includes different control strategies and optimization schemes. As non-limiting examples, the control strategy types in the policy library include, but are not limited to, path planning, task scheduling, and resource allocation. The control strategies specifically include decision rules, algorithms, and policy parameters.

[0102] In some specific implementation processes, a real-time interactive system for policy integration is built to manage policy generation. The workflow is as follows: Figure 7 As shown in the figure. In the strategy integration real-time interactive system, the execution of the overall control task and the strategy generation and decision-making process are precisely divided into several main steps:

[0103] (1) The system's underlying real-time data acquisition mechanism collects data from various sources and stores it in a database and cache layer. This data includes real-time situational information from the outside world, such as video data, target recognition data, GPS information, and drone flight information. The storage and management of this information ensures that the system can quickly respond to environmental changes.

[0104] (2) When the external task-driven policy control node puts forward "demands" to the policy integration real-time interactive system, these demands are passed to the "policy generation and decision module" within the system. In this module, the demands are combined with the real-time information stored in the "environmental parameter library" to generate the corresponding strategy.

[0105] (3) When external tasks drive external control nodes to submit requirements to the policy integration real-time interactive system, the policy generation and decision module receives these requirements and performs policy deduction based on the data from the environmental parameter library. The core function of this module is to generate optimal policy decision information by integrating different intelligent control strategies through the policy fusion framework.

[0106] (4) By continuously collecting environmental data, the system can monitor environmental changes in real time. During the strategy execution process, the system continuously receives feedback from the external environment. This feedback can be execution results, indicators of environmental changes, or other forms of data. This feedback data will be sent back to the system for analysis and optimization of existing strategies. The form of feedback data can include but is not limited to sensor readings, operation result reports, user feedback, etc. After analysis, the received external feedback data will affect the strategy optimization process.

[0107] In some optional embodiments, determining the policy decision information further includes:

[0108] The policy control node uploads the policy decision information to the central service node, and the central service node performs policy deduction based on the policy decision information to simulate the result of policy execution, generates a deduction result, and sends it to the policy control node;

[0109] In response to receiving the deduction result, the policy control node optimizes the policy decision information and uses the optimized policy decision information as output policy decision information (ie, the policy ultimately executed by the edge node).

[0110] Exemplarily, the results of strategy execution may be simulated using Monte Carlo simulation, optimization algorithms, or predictive models.

[0111] In some optional embodiments, after executing the policy decision information, the one or more policy control nodes perform policy interaction with the central service node of the corresponding task area, including:

[0112] The one or more policy control nodes receive the environmental parameter information or execution feedback information after executing the policy decision information from the central service node, and perform secondary optimization on the control policy in the policy library according to the environmental parameter information or the execution feedback information.

[0113] As a non-limiting example, a genetic algorithm or a particle swarm optimization algorithm may be used to perform secondary optimization on the policy parameters and / or decision rules of the control policy.

[0114] It should be understood that in the above embodiment, the primary optimization / secondary optimization not only improves the system's adaptability to dynamic network states, but also improves the accuracy and timeliness of policy execution, thereby better supporting task scheduling and control.

[0115] In some preferred embodiments, the policy issuance includes single policy issuance and / or policy distribution;

[0116] The single strategy includes:

[0117] The one or more policy control nodes send the decision information to the corresponding edge nodes in the corresponding task area;

[0118] The policy distribution includes:

[0119] The one or more policy control nodes upload the policy decision information to the central service node to determine the integrated policy, integrated policy = {policy cj ,c j ∈C i},Strategy cj represents the policy decision information applied to the j-th edge node controlled by the i-th policy control node; and

[0120] The central service node packages the integrated policy into a message format, and after determining the target policy control node and / or target edge node that needs to receive the integrated policy, distributes the integrated policy to the target policy control node and / or the target edge node for policy unpacking. The distribution process can be expressed as follows:

[0121] In some preferred embodiments, the distributed data synchronization mechanism includes:

[0122] The central service node packages the node overview status information and the policy decision information in the corresponding task area into a synchronization data packet, and transmits the synchronization data packet to another central service node in a different task area in a broadcast mode. This process can be expressed as

[0123] The other central service node unpacks the received synchronization data packet after verification and uses a consistency algorithm to resolve data conflicts. This process can be expressed as

[0124] It should be noted that data synchronization mainly occurs between central service nodes S in different task areas R. Assume that there are multiple task areas R i , each task area R i The central server (ie the central service node) is represented as S i The goal of data synchronization is to ensure data consistency between these central servers to expand cascaded multiple regions.

[0125] Those skilled in the art will understand that during the data transmission and storage process, data integrity and correctness verification is required, including but not limited to verifying the checksum and / or digital signature of the data, to ensure that the data has not been tampered with during transmission. The process can be expressed as follows:

[0126] Validate(D sync (S j ))→ValidationResult.

[0127] Exemplarily, the consistency algorithm includes but is not limited to consistent hashing and conflict resolution mechanism, and its process can be expressed as follows:

[0128]

[0129] In some optional embodiments, after sending or receiving the synchronization data packet, the central service node records the version information of each data synchronization to implement a version control mechanism. This helps track data changes and enables rollback to the previous version in the event of data inconsistency. The process can be expressed as follows:

[0130] V sync (S j )=VersionControl(D sync (S j )).

[0131] In some optional embodiments, an incremental synchronization mechanism is adopted between the central service nodes, that is, the node overview status information and the changed part of the policy decision information in the corresponding task area are packaged into a synchronization data packet instead of the entire data, so as to reduce the amount of transmitted data and improve synchronization efficiency.

[0132] IncrementalSync(D sync (S j ))→DeltaData.

[0133] In some optional embodiments, the central service nodes use an asynchronous transmission mechanism to synchronize data to reduce the impact of synchronization operations on system performance. The process can be expressed as follows:

[0134] AsyncSend(D sync (S i )→S j ).

[0135] Furthermore, in order to cope with the asymmetry between sending and receiving, a buffer strategy is adopted in asynchronous transmission.

[0136] In some optional embodiments, the central service node compresses the data to be synchronized before packaging it into a synchronization data packet to reduce the amount of data transmitted and increase the transmission speed:

[0137] Compress(D sync (S i ))→CompressData.

[0138] Based on the above-mentioned incremental synchronization mechanism, asynchronous transmission mechanism and / or data compression mechanism, the efficiency and reliability of the data synchronization process can be further improved, and multi-region expansion and collaboration can be supported.

[0139] It's important to emphasize that the use of a distributed data synchronization mechanism ensures data consistency and efficient task execution in a multi-region, multi-center server environment. Through effective data synchronization and consistency management, the method described in this embodiment achieves data coordination and integration across different regions, improving overall reliability and system performance. This distributed data synchronization mechanism ensures accurate information transmission and efficient task allocation, enhancing system stability and operational efficiency in large-scale networks.

[0140] Example 2

[0141] This embodiment provides a computer-readable storage medium, on which is stored at least one instruction, at least one program, code set, or instruction set. The at least one instruction, at least one program, code set, or instruction set is loaded and executed by a processor, so that the processor performs some or all steps of the method provided in Example 1 of the present application.

[0142] It is understood that the storage medium may be transient or non-transient. Exemplarily, the storage medium includes, but is not limited to, a USB flash drive, a mobile hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, among other media capable of storing program code.

[0143] Exemplarily, the processor may be a central processing unit (CPU), a microprocessor (MPU), a digital signal processor (DSP), or a field programmable gate array (FPGA).

[0144] Exemplarily, the read-only memory includes but is not limited to MASK ROM, PROM, EPROM, EEPROM, Flash, etc.

[0145] Exemplarily, the random access memory includes but is not limited to DRAM, SRAM, SDRAM, DDR SDRAM, etc.

[0146] In some examples, a computer program product is provided, which can be implemented in hardware, software, or a combination thereof. As a non-limiting example, the computer program product can be embodied as the storage medium, or as a software product, such as an SDK (Software Development Kit).

[0147] As a non-limiting example, a computer program product is provided, comprising a computer program or computer-executable instructions stored in a computer-readable storage medium. A processor of an electronic device reads the computer program or computer-executable instructions from the computer-readable storage medium and executes the computer-executable instructions, causing the electronic device to perform some or all of the steps of the method described in the embodiments of the present application.

[0148] In some examples, a computer program is provided, comprising a computer-readable code. When the computer-readable code is run in a computer device, a processor in the computer device executes the steps for implementing some or all of the steps in the method.

[0149] This embodiment also proposes an electronic device, including a memory and a processor, wherein the memory stores at least one instruction, at least one program, code set or instruction set, and when the processor executes the at least one instruction, at least one program, code set or instruction set, it implements part or all of the steps of the method described in Example 1.

[0150] In some examples, a hardware entity of the electronic device is provided, including: a processor, a memory and a communication interface; wherein the processor generally controls the overall operation of the electronic device; the communication interface is used to enable the electronic device to communicate with other terminals or servers through a network; the memory is configured to store instructions and applications executable by the processor, and can also cache data to be processed or processed by the processor and various modules in the electronic device (including but not limited to image data, audio data, voice communication data and video communication data), which can be implemented by flash memory (FLASH), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM) or random access memory (RAM).

[0151] A processor may include one or more processing elements. Thus, a processor may include one or more integrated circuits (ICs) configured to perform the functions of the processor. Furthermore, each integrated circuit may include circuits (e.g., a first circuit, a second circuit, and other circuits) configured to perform the functions of the processor.

[0152] Furthermore, data may be transmitted between the processor, the communication interface and the memory via a bus, which may include any number of interconnected buses and bridges, connecting various circuits of one or more processors and memories.

[0153] It can be understood that the options in the above embodiment 1 are also applicable to this embodiment, so they will not be described again here.

[0154] The same or similar reference numerals correspond to the same or similar components;

[0155] The terms used in the drawings to describe positional relationships are for illustrative purposes only and are not to be construed as limiting the present application.

[0156] It should be noted that, unless there is any conflict, the embodiments and features in the embodiments of this application can be combined with each other.

[0157] In different specific implementations, the method or system described in this application can be implemented in software, hardware or a combination thereof. In addition, the order of the steps of the method can be changed, and various elements can be added, reordered, combined, omitted, modified, etc.

[0158] Obviously, the above embodiments of the present application are merely examples for clearly illustrating the present application, and are not intended to limit the implementation methods of the present application, and are not intended to limit the present application. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. Each discrete structural / functional module or unit can be integrated together to form an independent part, or each module can exist alone, or two or more modules can be integrated to form an independent part, and the structure and function of the discrete components can be implemented as a combined structure or component. It is not necessary and impossible to enumerate all the implementation methods here. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present application should be included in the scope of protection of the claims of the present application.

Claims

1. A node control method in a wireless network cluster, characterized in that: include: Establishing a central distributed wireless network cluster model; wherein the central distributed wireless network cluster model is divided into one or more task areas, wherein one or more policy control nodes, one or more edge nodes, and a central service node are distributed within the task area, and the nodes in the task area communicate with each other based on a self-organizing network strategy; The central service node generates node overview status information in response to receiving local status information transmitted by the one or more edge nodes in the corresponding task area; In response to receiving the node overview status information from the central service node of the corresponding task area, the one or more policy control nodes establish connections with the one or more edge nodes to obtain detailed status information about the edge nodes; The one or more policy control nodes determine policy decision information according to the detailed status information, and distribute the policy to the one or more edge nodes and / or the one or more policy control nodes in the corresponding area; When there are multiple task areas, the corresponding central service nodes of different task areas perform data synchronization based on a distributed data synchronization mechanism; The determination of the policy decision information includes: According to the task requirements of the overall control task, the central service node selects at least one control strategy from the preset strategy library in combination with the environmental parameter information for evaluation and determines the optimal control strategy. , the selection process is expressed as: Where, represents an evaluation function for evaluating the adaptability and effectiveness of the control strategy; Indicates the environmental parameter information; Indicates the A control strategy, Represents a set of control strategies preset in the strategy library; Represents the overall control task; For the mission area For all the strategy control nodes in , the corresponding optimal control strategy is expressed as: Where, Indicates that it is applicable to the mission area No. A control strategy, Indicates the task area Corresponding environmental parameter information; The policy control node performs task allocation based on the optimal control strategy and the detailed status information of the one or more edge nodes to determine the policy decision information. , the process is expressed as: Where, Represents the process of allocating control tasks; Indicates the task area Corresponding control tasks; Indicates the The policy control node.

2. The node control method in a wireless network cluster according to claim 1, characterized in that: The self-organizing network strategy includes: At least one node in the central distributed wireless network cluster model acts as a coordination node, broadcasts networking notifications and configures network parameters to initialize the network; Responding to a network joining request broadcast by a node not yet on the network At least one node that has joined the network performs authentication on the node that has not joined the network according to the network access request, and returns an authentication response message after the authentication is successful. ;in, A unique identifier representing a node, The message content indicating the join request; Represents the authentication process; Represents a security key; In response to the node not connected to the network broadcasting the identity authentication response message to the network, the remaining nodes that have connected to the network decrypt or verify the identity authentication response message, determine that the information in the identity authentication response message is valid and meets expectations, accept the node not connected to the network to join the network, and update the routing table.

3. The node control method in a wireless network cluster according to claim 1, characterized in that: The central service node generates node overview status information in response to receiving local status information transmitted by the one or more edge nodes in the corresponding task area, including: The one or more edge nodes continuously monitor their own operating status to generate current status information, and package their own unique identification code and current status information into local status information. ;in, Indicates the edge node Unique identification code , Indicates the current status information; After the one or more edge nodes establish a connection with the central service node of the corresponding task area through a wireless network, the packaged local state information is sent to the central service node. The process is as follows: ;in, Indicates sending the local status information to the central service node ; The central service node receives the local status information from the one or more edge nodes, performs hash storage and generates a status table, dynamically allocates a temporary ID to the corresponding edge node according to the unique identification code, and generates the node overview status information.

4. The node control method in a wireless network cluster according to claim 3, characterized in that: The one or more policy control nodes, in response to receiving the node overview status information from the central service node of the corresponding task area, establish a connection with the edge node to obtain detailed status information about the edge node, including: The policy control node requests the central service node to obtain the node overview information, determines the target edge node to be connected to based on the node overview information, and transmits the corresponding coding information of the temporary ID of the target edge node to the central service node; After decoding, the central server uses the state table to determine the real IP address of the target edge node, communicates with the target edge node based on the real IP address for authentication, and encrypts the real IP address and returns it to the policy control node after successful authentication; After verifying the fingerprint information, the policy control node decrypts the real IP address and sends a connection request to the target edge node based on the real IP address to obtain at least partial control rights of the target edge node and the detailed status information.

5. The node control method in a wireless network cluster according to claim 1, characterized in that: The determining of the strategy decision information further includes: The policy control node uploads the policy decision information to the central service node, and the central service node performs policy deduction based on the policy decision information to simulate the result of policy execution, generates a deduction result, and sends it to the policy control node; In response to receiving the deduction result, the policy control node optimizes the policy decision information once, and uses the optimized policy decision information as output policy decision information.

6. The node control method in a wireless network cluster according to claim 1, characterized in that: After executing the policy decision information, the one or more policy control nodes perform policy interaction with the central service node of the corresponding task area, including: The one or more policy control nodes receive the environmental parameter information or execution feedback information after executing the policy decision information from the central service node, and perform secondary optimization on the control policy in the policy library according to the environmental parameter information or the execution feedback information.

7. The node control method in a wireless network cluster according to claim 1, characterized in that: The policy issuance includes single policy issuance and / or policy distribution; wherein, The strategy includes: The one or more policy control nodes send the decision information to the corresponding edge nodes in the corresponding task area; The policy distribution includes: The one or more policy control nodes upload the policy decision information to the central service node to determine an integrated policy; and The central service node packages the integrated policy into a message format, and after determining the target policy control node and / or target edge node that needs to receive the integrated policy, distributes the integrated policy to the target policy control node and / or the target edge node for policy unpacking.

8. The node control method in a wireless network cluster according to claim 1, characterized in that: The distributed data synchronization mechanism includes: The central service node packages the node overview status information and the policy decision information in the corresponding task area into a synchronization data packet, and transmits the synchronization data packet to another central service node in a different task area in a broadcast mode; The other central service node depacks the received synchronization data packet after verification and adopts a consistency algorithm to resolve data conflicts.

9. A computer program product comprising a computer program or computer executable instructions, characterized in that When the computer program or computer executable instructions are executed by a processor, the method according to any one of claims 1 to 8 is implemented.

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