Clustering network topology agile discovery method and device based on battlefield roaming intelligent body

Abstract

The invention provides a clustering network topology agile discovery method and device based on battlefield roaming intelligent bodies, and relates to the technical field of wireless self-organizing networks. The method comprises the following steps: acquiring network topology information of a wireless ad hoc network; obtaining a network topology discovery result according to the roaming agent in the wireless ad hoc network and the hierarchical preferential search strategy of the roaming agent; after a preset time interval, the number of the roaming intellectual bodies is adjusted according to the number of the roaming intellectual bodies and a network topology discovery quality evaluation mechanism; and obtaining an optimized network topology discovery result according to the adjusted roaming intellectual body and the hierarchical preferential search strategy of the roaming intellectual body. According to the method, network topology discovery can be rapidly and accurately completed under the conditions that the battlefield spectrum environment changes violently, the nodes fail to exit frequently and the network moves fast, the requirement for high-quality communication in the battlefield environment is met, and it is guaranteed that topology discovery can be continuously, rapidly and accurately carried out on the network.

Description

Technical Field

[0001] The present invention relates to the technical field of wireless self-organizing networks, and in particular to a clustering network topology agile discovery method and device based on battlefield roaming agents. Background Art

[0002] In the battle scenario of fighting for tactical positions, the cognitive wireless self-organizing network formed by combat units often faces challenges such as enemy electromagnetic interference, physical attacks and rapid network movement. The traditional topology discovery method based on information feedback uses the sending and receiving of data packets, which requires each node in the network to have two-way communication capabilities. When the network environment is unstable, problems such as high network packet loss rate and low reliability are prone to occur. Summary of the invention

[0003] In order to solve the problems of drastic spectrum changes and frequent node failures in battlefield cognitive wireless self-organizing networks, as well as the need for continuous high-quality topology discovery in high-intensity combat, an embodiment of the present invention provides a clustered network topology agile discovery method and device based on battlefield roaming agents. The technical solution is as follows:

[0004] On the one hand, a clustered network topology agile discovery method based on a battlefield roaming agent is provided, the method is implemented by a clustered network topology agile discovery device, and the method includes:

[0005] S1. Obtain network topology information of a wireless ad hoc network for which network topology discovery is to be performed.

[0006] S2. According to the roaming agents in the wireless self-organizing network and the hierarchical optimal search strategy of the roaming agents, the network topology discovery result is obtained.

[0007] S3. After a preset time interval, the number of roaming agents is adjusted according to the number of roaming agents and the network topology discovery quality evaluation mechanism.

[0008] S4. According to the adjusted roaming agent and the hierarchical optimal search strategy of the roaming agent, an optimized network topology discovery result is obtained.

[0009] Optionally, the wireless self-organizing network in S1 includes multiple nodes, and the multiple nodes are divided into multiple clusters.

[0010] For each of the multiple clusters, a node is selected as the cluster head, and the other nodes except the selected cluster head are cluster members; the cluster head generates a roaming agent when it is selected.

[0011] Select a gateway node from the cluster head or cluster members.

[0012] Optionally, a gateway node is selected from the cluster head or cluster members, including:

[0013] During the intra-cluster topology exchange, after the cluster members are initialized, they monitor the frequency hopping sequence to determine whether any cluster member has received the query information from the cluster head of other clusters.

[0014] If so, the cluster member that receives the query information is a gateway node, and updates the neighbor cluster head table.

[0015] If not, the cluster head is the gateway node.

[0016] The gateway node feeds back topology information to the cluster head to which the gateway node belongs every preset intra-cluster response time interval.

[0017] When exchanging topology between clusters, the gateway node exchanges topology information with roaming agents and neighboring cluster heads.

[0018] The gateway node also sends a flag bit to the cluster head to which the gateway node belongs, to ensure that the gateway node and the cluster head to which the gateway node belongs can continue to exchange topology information with the roaming agent when the connection is lost.

[0019] Optionally, the hierarchical optimization search strategy of the roaming agent in S2 includes:

[0020] The priority of the gateway node is defined as 1, and the priority of the cluster member is defined as 0. For any node a0, its neighbor node a i The distance between (i=1,2,…n) and node a0 is d i (i=1,2,…n), n represents the total number of nodes.

[0021] If node a0's neighbor node a i If there is only one node with a priority of 1 and has not been traversed, then this node is selected as the next hop node.

[0022] If node a0's neighbor node a i If there are multiple nodes with the same priority and have not been traversed, then select the node a with the smallest distance among the nodes with the same priority. j is the next hop node, (j=1,2,…n).

[0023] Optionally, the network topology discovery quality evaluation mechanism includes:

[0024] The path convergence of the wireless ad hoc network is calculated as shown in the following formula (1):

[0025]

[0026] In the formula, α represents the path convergence, ∑α p It represents the sum of the node pair connectivity obtained by all nodes in the wireless ad hoc network at a certain moment, and n represents the total number of nodes.

[0027] Calculate the perception accuracy as shown in the following formula (2):

[0028]

[0029] In the formula, P represents the perception accuracy, and M0 represents the adjacency matrix of node m. Satisfied middle The number of P Represents the adjacency matrix of node m Satisfied middle The number of, M1 represents the actual adjacency matrix A(t) = (a pq ) n×n Satisfy a pq =1(p,q=1,2,…n) pq The number of P Represents the adjacency matrix of node m Satisfied middle The number of

[0030] The available spectrum accuracy of all nodes in the network topology discovery process in the wireless ad hoc network is calculated as shown in the following formula (3):

[0031]

[0032] In the formula, γ represents the accuracy of available spectrum, ∑γ m It represents the sum of the available spectrum accuracy of all cognitive nodes at a certain moment obtained by the topology discovery process in the network.

[0033] Optionally, in S3, after a preset time interval, the number of roaming agents is adjusted according to the number of roaming agents and a network topology discovery quality evaluation mechanism, including:

[0034] After the preset agent number self-check time interval, it is determined whether the number of roaming agents is less than the number of cluster heads. If so, a new roaming agent is generated and the topology information is copied.

[0035] After a preset network performance evaluation time interval, determine whether the path convergence α is less than a preset path convergence threshold α min , or the perception accuracy P is less than the preset perception accuracy threshold P min , or the available spectrum accuracy γ is less than the preset spectrum accuracy threshold γ min , if so, a new roaming agent is generated and the topology information is copied.

[0036] On the other hand, a clustered network topology agile discovery device based on battlefield roaming agents is provided, and the device is applied to a clustered network topology agile discovery method based on battlefield roaming agents, and the device includes:

[0037] The acquisition module is used to acquire the network topology information of the wireless self-organizing network to be discovered.

[0038] The topology discovery module is used to obtain the network topology discovery result according to the roaming agents in the wireless self-organizing network and the hierarchical optimal search strategy of the roaming agents.

[0039] The adjustment module is used to adjust the number of roaming agents according to the number of roaming agents and the network topology discovery quality evaluation mechanism after a preset time interval.

[0040] The output module is used to obtain an optimized network topology discovery result according to the adjusted roaming agent and the hierarchical optimal search strategy of the roaming agent.

[0041] Optionally, the wireless ad hoc network includes a plurality of nodes, and the plurality of nodes are divided into a plurality of clusters.

[0042] For each of the multiple clusters, a node is selected as the cluster head, and the other nodes except the selected cluster head are cluster members; the cluster head generates a roaming agent when it is selected.

[0043] Select a gateway node from the cluster head or cluster members.

[0044] Optionally, a gateway node is selected from the cluster head or cluster members, including:

[0045] During the intra-cluster topology exchange, after the cluster members are initialized, they monitor the frequency hopping sequence to determine whether any cluster member has received the query information from the cluster head of other clusters.

[0046] If so, the cluster member that receives the query information is a gateway node, and updates the neighbor cluster head table.

[0047] If not, the cluster head is the gateway node.

[0048] The gateway node feeds back topology information to the cluster head to which the gateway node belongs every preset intra-cluster response time interval.

[0049] When exchanging topology between clusters, the gateway node exchanges topology information with roaming agents and neighboring cluster heads.

[0050] The gateway node also sends a flag bit to the cluster head to which the gateway node belongs, to ensure that the gateway node and the cluster head to which the gateway node belongs can continue to exchange topology information with the roaming agent when the connection is lost.

[0051] Optionally, the hierarchical optimization search strategy of the roaming agent includes:

[0052] The priority of the gateway node is defined as 1, and the priority of the cluster member is defined as 0. For any node a0, its neighbor node a i The distance between (i=1,2,…n) and node a0 is d i (i=1,2,…n), n represents the total number of nodes.

[0053] If node a0's neighbor node a i If there is only one node with a priority of 1 and has not been traversed, then this node is selected as the next hop node.

[0054] If node a0's neighbor node a i If there are multiple nodes with the same priority and have not been traversed, then select the node a with the smallest distance among the nodes with the same priority. j is the next hop node, (j=1,2,…n).

[0055] Optionally, the network topology discovery quality evaluation mechanism includes:

[0056] The path convergence of the wireless ad hoc network is calculated as shown in the following formula (1):

[0057]

[0058] In the formula, α represents the path convergence, ∑α p It represents the sum of the node pair connectivity obtained by all nodes in the wireless ad hoc network at a certain moment, and n represents the total number of nodes.

[0059] Calculate the perception accuracy as shown in the following formula (2):

[0060]

[0061] In the formula, P represents the perception accuracy, and M0 represents the adjacency matrix of node m. Satisfied middle The number of P Represents the adjacency matrix of node m Satisfied middle The number of, M1 represents the actual adjacency matrix A(t) = (a pq ) n×n Satisfy a pq =1(p,q=1,2,…n) pq The number of P Represents the adjacency matrix of node m Satisfied middle The number of

[0062] The available spectrum accuracy of all nodes in the network topology discovery process in the wireless ad hoc network is calculated as shown in the following formula (3):

[0063]

[0064] In the formula, γ represents the accuracy of available spectrum, ∑γ m It represents the sum of the available spectrum accuracy of all cognitive nodes at a certain moment obtained by the topology discovery process in the network.

[0065] Optionally, the adjustment module is further configured to:

[0066] After the preset agent number self-check time interval, it is determined whether the number of roaming agents is less than the number of cluster heads. If so, a new roaming agent is generated and the topology information is copied.

[0067] After a preset network performance evaluation time interval, determine whether the path convergence α is less than a preset path convergence threshold α min , or the perception accuracy P is less than the preset perception accuracy threshold P min , or the available spectrum accuracy γ is less than the preset spectrum accuracy threshold γ min , if so, a new roaming agent is generated and the topology information is copied.

[0068] On the other hand, a clustered network topology agile discovery device is provided, the clustered network topology agile discovery device comprising: a processor; a memory, the memory storing computer-readable instructions, and when the computer-readable instructions are executed by the processor, any one of the above-mentioned clustered network topology agile discovery methods based on battlefield roaming agents is implemented.

[0069] On the other hand, a computer-readable storage medium is provided, in which at least one instruction is stored, and the at least one instruction is loaded and executed by a processor to implement any of the above-mentioned clustered network topology agile discovery methods based on battlefield roaming agents.

[0070] The beneficial effects brought about by the technical solution provided by the embodiment of the present invention include at least:

[0071] In the present invention, in order to improve the problems existing in the traditional topology discovery method, a topology discovery method based on roaming agents is proposed. Roaming agents are intelligent agents that can autonomously migrate and perform tasks in a computer network. They have mobility, autonomy, intelligence and collaboration. One or more agents are used to move freely in the network according to a certain strategy, collect topology information of nodes or node neighbors at each node in the network, and send other node information and network topology information carried by themselves to the current node to realize the propagation of network topology.

[0072] In view of the characteristics of rapid topology changes and frequent node failures in battle scenarios for tactical locations and the need for continuous high-quality topology discovery, the present invention proposes a topology discovery method based on roaming agents for battlefield networks and a network topology discovery quality evaluation mechanism and optimization method, so that the cognitive wireless self-organizing network in the battle scenario for tactical locations can still maintain fast and accurate topology discovery when facing frequent node failures. BRIEF DESCRIPTION OF THE DRAWINGS

[0073] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0074] Figure 1 This is a flow chart of a clustered network topology agile discovery method based on battlefield roaming agents provided by an embodiment of the present invention;

[0075] Figure 2 It is a flow chart of a clustered network topology agile discovery method based on battlefield roaming agents provided by an embodiment of the present invention;

[0076] Figure 3 is a flow chart of a roaming agent traversal strategy provided by an embodiment of the present invention;

[0077] Figure 4 This is a block diagram of a clustered network topology agile discovery device based on battlefield roaming agents provided by an embodiment of the present invention;

[0078] Figure 5 The present invention provides a schematic diagram of the structure of a cluster network topology agile discovery device. DETAILED DESCRIPTION

[0079] The technical solution of the present invention is described below in conjunction with the accompanying drawings.

[0080] In the embodiments of the present invention, words such as "exemplarily" and "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "example" in the present invention should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of the word "example" is intended to present the concept in a specific way. In addition, in the embodiments of the present invention, the meaning expressed by "and / or" can be both, or it can be either of the two.

[0081] In the embodiments of the present invention, "image" and "picture" can sometimes be used interchangeably. It should be noted that when the difference between them is not emphasized, the meanings they intend to express are the same. "of", "corresponding, relevant" and "corresponding" can sometimes be used interchangeably. It should be noted that when the difference between them is not emphasized, the meanings they intend to express are the same.

[0082] In the embodiments of the present invention, sometimes a subscript such as W1 may be written as a non-subscript such as W1. When the difference is not emphasized, the meanings to be expressed are the same.

[0083] In order to make the technical problems, technical solutions and advantages to be solved by the present invention more clear, a detailed description will be given below with reference to the accompanying drawings and specific embodiments.

[0084] The embodiment of the present invention provides a clustered network topology agile discovery method based on battlefield roaming agents. The method can be implemented by a clustered network topology agile discovery device, which can be a terminal or a server. Figure 1 , Figure 2 The flowchart of the clustered network topology agile discovery method based on battlefield roaming agents is shown. The processing flow of the method may include the following steps:

[0085] S1. Obtain network topology information of a wireless ad hoc network for which network topology discovery is to be performed.

[0086] Optionally, the wireless self-organizing network in S1 includes multiple nodes, and the multiple nodes are divided into multiple clusters.

[0087] For each of the multiple clusters, a node is selected as the cluster head, and the other nodes except the selected cluster head are cluster members; the cluster head generates a roaming agent when it is selected.

[0088] Select a gateway node from the cluster head or cluster members.

[0089] In a feasible implementation, the topology of the battlefield cognitive wireless self-organizing network at a specific time is an undirected graph G(t)=(V t ,E t ), where the node p at time t consists of vertices v p (t)∈V(t), the communication link between cognitive nodes p and q at time t is represented by edge e pq (t)∈E(t) represents.

[0090] First, initialize all potential available channels C in the environment around our node, which contains n c subchannels, each of which contains k cA set of channels, setting a fixed path convergence threshold α min , Perception accuracy threshold P min , spectrum accuracy threshold γ min , intra-cluster response time interval T, agent quantity self-check time interval T0 and network performance evaluation time interval T1, etc.

[0091] Furthermore, the total number n of cognitive nodes in the network and the total number N of channels in the network are calculated within a preset reasonable range.

[0092] Furthermore, when topology exchange is performed within the cluster, after the cluster members are initialized, they monitor on each frequency from the frequency hopping sequence. If a query message sent by other cluster heads is received at this time, the cluster member evolves into a gateway node, updates its own neighbor cluster head table, and feeds it back to its original cluster head (if there are multiple original cluster heads, it feeds back to multiple heads). Feedback its own topology information to its own cluster head after a fixed period. After a fixed period, the topology information message is sent to the cluster head only when the neighbors and spectrum availability change, otherwise the message information is silently not sent.

[0093] When topology exchange is performed between clusters, for the gateway node, if a roaming agent arrives, the agent is processed, the topology information of other parts of the network at the agent is obtained, the topology table of the entire network is updated, and the topology information of the cluster related to itself is passed to the agent. At the same time, the newly obtained topology information of the entire network is sent to the cluster head connected to it, and the topology information at the cluster head is updated.

[0094] If query information is received from other neighboring cluster heads, the cluster head table is updated and the updated cluster head table is sent to each cluster head.

[0095] If a cluster head receives a message about the update of its intra-cluster topology information, the intra-cluster topology table of the current cluster is updated and sent to other cluster heads connected to the gateway to speed up the convergence of topology information. At the same time, the gateway sends a flag message to the cluster head so that the cluster head can continue to exchange topology information with the roaming agent without crashing after the gateway loses connection with the cluster head.

[0096] For the cluster head node, when the intelligent agent arrives at the cluster head, it will first check the flag bit at the cluster head. If the cluster head does not have a gateway, it will exchange topology information with the cluster head, otherwise it will leave directly.

[0097] Topology exchange is performed at the cluster head. The specific method is the same as that of the gateway. However, when the cluster head receives the information that the cluster member becomes a gateway, the cluster head automatically exits the intelligent body exchange state and sends its own topology information and flag information to the new gateway. The new gateway enters the intelligent body topology information exchange state.

[0098] Furthermore, each cluster head generates a roaming agent when it is selected, and each agent traverses the entire network according to the roaming agent traversal strategy, and the number of agents is replenished every time T0 passes.

[0099] S2. According to the roaming agents in the wireless self-organizing network and the hierarchical optimal search strategy of the roaming agents, the network topology discovery result is obtained.

[0100] Optionally, the hierarchical optimization search strategy of the roaming agent in S2 includes:

[0101] like Figure 3 As shown in Figure 1, the agent uses a hierarchical optimization search strategy to traverse. This strategy is based on breadth-first search. The priority of the gateway node (which can be a cluster member or cluster head) is defined as 1, and the priority of the cluster member is defined as 0. For any node a0, its neighbor node a i The distance between (i=1,2,…n) and node a0 is d i (i=1,2,…n), n represents the total number of nodes.

[0102] Furthermore, for nodes at the same layer in breadth-first search, the strategy for selecting the next hop is:

[0103] If node a0's neighbor node a i If there is only one node with a priority of 1 and has not been traversed, then this node is selected as the next hop node.

[0104] If node a0's neighbor node a i If there are multiple nodes with the same priority and have not been traversed, then select the node a with the smallest distance among the nodes with the same priority. j is the next hop node, (j=1,2,…n).

[0105] S3. After a preset time interval, the number of roaming agents is adjusted according to the number of roaming agents and the network topology discovery quality evaluation mechanism.

[0106] In a feasible implementation, the performance of the topology discovery method is measured by comparing the actual topology of the network (i.e., the actual connection status of each cognitive node in the network and its available spectrum) with the acquired topology to reflect its accuracy. The actual connection status between cognitive nodes in the network at time t is represented by the adjacency matrix A(t) = (a pq ) n×n express.

[0107] The present invention determines whether the topology discovery process is abnormal by defining the thresholds of the three parameters of path convergence, perception accuracy, and available spectrum accuracy, and compares them with the actual values, and makes adjustments. The steps for calculating path convergence are as follows:

[0108] Calculate the connectivity between nodes p and q in the network obtained by cognitive node m in the network through topology discovery method It is expressed as:

[0109]

[0110] Among them l pg represents the connectivity between nodes p and q in the actual network. represents the connectivity between nodes p and q in the network obtained by node m in the network. The communication link is considered to be converged.

[0111] Furthermore, we calculate the connectivity α between node m and all node pairs. m , expressed as:

[0112]

[0113] in Indicates the connectivity between all node pairs obtained by the node in the current stage, represents the total number of node pairs in the cognitive wireless ad hoc network. For any time, α m =1 means that the topology information obtained by the current node m is exactly the same as the actual topology in terms of connectivity.

[0114] Furthermore, according to the sum of node pair connectivity obtained by all cognitive nodes in the network at a certain moment, ∑α p , and the total number of cognitive nodes n in the network to calculate the path convergence α of the entire network, expressed as:

[0115]

[0116] In the formula, α represents the path convergence, ∑α p It represents the sum of the node pair connectivity obtained by all nodes in the wireless ad hoc network at a certain moment, and n represents the total number of nodes.

[0117] The steps to calculate the perception accuracy are as follows:

[0118] Estimate the actual adjacency matrix A(t) = (a pq ) n×n All satisfy the following constraints a pq =1(p,q=1,2,…n) pq The number M1 and the adjacency matrix of node m All satisfy the following restrictions middle The number of p, we can get the ratio P0 of the number of communication connections that exist in the actual topology but are not perceived to the total number of connections in the actual topology:

[0119]

[0120] Calculate the adjacency matrix of node m All satisfy the following restrictions middle The number M0 and the adjacency matrix of node m All satisfy the following restrictions middle The number is considered to be F p , we can get the ratio P1 of the number of connections that exist in the topology network obtained through topology discovery but do not exist in the actual topology to the total number of connections in the perceived topology:

[0121]

[0122] Furthermore, the perception accuracy P is calculated, that is, the ratio of the number of communication connections that exist and are perceived in the actual topology to the total number of connections in the actual topology:

[0123] P=1-(P0+P1) (6)

[0124] Substituting equation (4) and equation (5) into the equation, we can obtain:

[0125]

[0126] In the formula, P represents the perception accuracy, and M0 represents the adjacency matrix of node m. Satisfied middle The number of P Represents the adjacency matrix of node m Satisfied middle The number of, M1 represents the actual adjacency matrix A(t) = (a pq ) n×n Satisfy a pq =1(p,q=1,2,…n) pq The number of P Represents the adjacency matrix of node m Satisfied middle The number of

[0127] The steps to calculate the available spectrum accuracy are as follows:

[0128] Calculate the number of channels that match the actual channel set of node m in the network obtained by cognitive node p through the topology discovery process In cognitive wireless self-organizing networks, the available spectrum of each cognitive node is constantly changing due to the emergence of primary users and environmental changes. In order to describe the accuracy of the available spectrum in the topology discovery process, the accuracy of the available spectrum of the node m in the network obtained by the cognitive node p in the network through the topology discovery process is expressed as To express:

[0129]

[0130] Where N represents the total number of channels in the network.

[0131] Furthermore, the accuracy of the available spectrum of the node obtained through the topology discovery process is calculated as:

[0132]

[0133] In the above formula, n represents the total number of cognitive nodes in the network.

[0134] Furthermore, the accuracy rate γ of the available spectrum of all nodes obtained by the topology discovery process in the network can be expressed as follows:

[0135]

[0136] Among them, ∑γ m It represents the sum of the available spectrum accuracy of all cognitive nodes at a certain moment obtained by the topology discovery process in the network.

[0137] Furthermore, each roaming agent carries historical information, the size of which is the sum of the number of located gateways and the number of cluster heads without gateway clusters, so as to avoid the next hop node selecting a node that has been visited recently.

[0138] The intelligent agent exchanges topology information with the gateway. In order to make the information up to date, the update time information should be added to the topology information.

[0139] Each gateway has N+1 flags (where N represents the number of agents in the network). N flags record whether the N agents in the network have accessed the gateway, and the other records the time when the topology information at the gateway is updated.

[0140] Optionally, in S3, after a preset time interval, the number of roaming agents is adjusted according to the number of roaming agents and a network topology discovery quality evaluation mechanism, including:

[0141] After the preset agent number self-check time interval, it is determined whether the number of roaming agents is less than the number of cluster heads. If so, a new roaming agent is generated and the topology information is copied.

[0142] In a feasible implementation, the gateway and the cluster head will check the number of roaming agents in the network. When the number of roaming agents is less than the number of cluster heads, new roaming agents will be generated and the topology information will be copied.

[0143] After a preset network performance evaluation time interval, determine whether the path convergence α is less than a preset path convergence threshold α min , or the perception accuracy P is less than the preset perception accuracy threshold P min , or the available spectrum accuracy γ is less than the preset spectrum accuracy threshold γ min , if so, a new roaming agent is generated and the topology information is copied.

[0144] The present invention takes into account the reduction of intelligent agents due to topology changes, sets an intelligent agent evaluation threshold mechanism, and dynamically adjusts the number of roaming intelligent agents in the network to meet the demand for high-quality communication in battlefield environments and ensure that the network can continuously, quickly and accurately perform topology discovery.

[0145] S4. According to the adjusted roaming agent and the hierarchical optimal search strategy of the roaming agent, an optimized network topology discovery result is obtained.

[0146] In an embodiment of the present invention, in order to improve the problems existing in the traditional topology discovery method, a topology discovery method based on roaming agents is proposed. A roaming agent is an agent that can autonomously migrate and perform tasks in a computer network. It has mobility, autonomy, intelligence and collaboration. It uses one or more agents to move freely in the network according to a certain strategy, collects topology information of nodes or node neighbors at each node in the network, and sends other node information and network topology information carried by itself to the current node to realize the propagation of network topology.

[0147] In view of the characteristics of rapid topology changes and frequent node failures in battle scenarios for tactical locations and the need for continuous high-quality topology discovery, the present invention proposes a topology discovery method based on roaming agents for battlefield networks and a network topology discovery quality evaluation mechanism and optimization method, so that the cognitive wireless self-organizing network in the battle scenario for tactical locations can still maintain fast and accurate topology discovery when facing frequent node failures.

[0148] Figure 4 The block diagram of a clustered network topology agile discovery device based on battlefield roaming agents according to an exemplary embodiment is shown. The device is used in a clustered network topology agile discovery method based on battlefield roaming agents. Figure 4The device includes an acquisition module 310, a topology discovery module 320, an adjustment module 330 and an output module 340. Among them:

[0149] The acquisition module 310 is used to acquire the network topology information of the wireless ad hoc network to be discovered.

[0150] The topology discovery module 320 is used to obtain a network topology discovery result according to the roaming agents in the wireless ad hoc network and the hierarchical optimal search strategy of the roaming agents.

[0151] The adjustment module 330 is used to adjust the number of roaming agents according to the number of roaming agents and the network topology discovery quality evaluation mechanism after a preset time interval.

[0152] The output module 340 is used to obtain an optimized network topology discovery result according to the adjusted roaming agent and the hierarchical optimal search strategy of the roaming agent.

[0153] In an embodiment of the present invention, in order to improve the problems existing in the traditional topology discovery method, a topology discovery method based on roaming agents is proposed. A roaming agent is an agent that can autonomously migrate and perform tasks in a computer network. It has mobility, autonomy, intelligence and collaboration. It uses one or more agents to move freely in the network according to a certain strategy, collects topology information of nodes or node neighbors at each node in the network, and sends other node information and network topology information carried by itself to the current node to realize the propagation of network topology.

[0154] In view of the characteristics of rapid topology changes and frequent node failures in battle scenarios for tactical locations and the need for continuous high-quality topology discovery, the present invention proposes a topology discovery method based on roaming agents for battlefield networks and a network topology discovery quality evaluation mechanism and optimization method, so that the cognitive wireless self-organizing network in the battle scenario for tactical locations can still maintain fast and accurate topology discovery when facing frequent node failures.

[0155] Figure 5 is a schematic diagram of the structure of a clustered network topology agile discovery device provided by an embodiment of the present invention, such as Figure 5 As shown, the cluster network topology agile discovery device may include the above Figure 4 The clustered network topology agile discovery device based on battlefield roaming agents is shown. Optionally, the clustered network topology agile discovery device 410 may include a first processor 2001 .

[0156] Optionally, the clustered network topology agile discovery device 410 may further include a memory 2002 and a transceiver 2003 .

[0157] The first processor 2001, the memory 2002 and the transceiver 2003 may be connected via a communication bus.

[0158] Combine the following Figure 5 The components of the clustered network topology agile discovery device 410 are described in detail:

[0159] The first processor 2001 is the control center of the clustered network topology agile discovery device 410, which can be a processor or a general term for multiple processing elements. For example, the first processor 2001 is one or more central processing units (CPUs), or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiment of the present invention, such as one or more microprocessors (digital signal processors, DSPs), or one or more field programmable gate arrays (field programmable gate arrays, FPGAs).

[0160] Optionally, the first processor 2001 may execute various functions of the clustered network topology agile discovery device 410 by running or executing a software program stored in the memory 2002 and calling data stored in the memory 2002 .

[0161] In a specific implementation, as an embodiment, the first processor 2001 may include one or more CPUs, such as Figure 5 CPU0 and CPU1 are shown in FIG.

[0162] In a specific implementation, as an embodiment, the clustered network topology agile discovery device 410 may also include multiple processors, such as Figure 5 The first processor 2001 and the second processor 2004 are shown in FIG. Each of these processors can be a single-core processor (single-CPU) or a multi-core processor (multi-CPU). The processor here can refer to one or more devices, circuits, and / or processing cores for processing data (e.g., computer program instructions).

[0163] The memory 2002 is used to store the software program for executing the solution of the present invention, and is controlled to be executed by the first processor 2001. The specific implementation method can refer to the above method embodiment, which will not be repeated here.

[0164] Optionally, the memory 2002 may be a read-only memory (ROM) or other types of static storage devices that can store static information and instructions, a random access memory (RAM) or other types of dynamic storage devices that can store information and instructions, or an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed optical disc, laser disc, optical disc, digital versatile disc, Blu-ray disc, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto. The memory 2002 may be integrated with the first processor 2001, or may exist independently, and may be accessed through the interface circuit ( Figure 5 (not shown) is coupled to the first processor 2001, which is not specifically limited in this embodiment of the present invention.

[0165] The transceiver 2003 is used to communicate with a network device or a terminal device.

[0166] Optionally, the transceiver 2003 may include a receiver and a transmitter ( Figure 5 The receiver is used to implement a receiving function, and the transmitter is used to implement a sending function.

[0167] Optionally, the transceiver 2003 may be integrated with the first processor 2001, or may exist independently, and discover the topology of the clustered network agilely through the interface circuit ( Figure 5 (not shown) is coupled to the first processor 2001, which is not specifically limited in this embodiment of the present invention.

[0168] It should be noted that Figure 5 The structure of the clustered network topology agile discovery device 410 shown in the figure does not constitute a limitation on the router, and the actual knowledge structure recognition device may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently.

[0169] In addition, the technical effects of the clustered network topology agile discovery device 410 can refer to the technical effects of the clustered network topology agile discovery method based on battlefield roaming agents described in the above method embodiment, which will not be repeated here.

[0170] It should be understood that the first processor 2001 in the embodiment of the present invention may be a central processing unit (CPU), and the processor may also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0171] It should also be understood that the memory in the embodiments of the present invention may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic random access memory (DRAM), synchronous DRAM (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link DRAM (SLDRAM), and direct rambus RAM (DR RAM).

[0172] The above embodiments can be implemented in whole or in part by software, hardware (such as circuits), firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present invention is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center by wired (such as infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (for example, a floppy disk, a hard disk, a tape), an optical medium (for example, a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0173] It should be understood that the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. A and B can be singular or plural. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship, but it may also indicate an "and / or" relationship. Please refer to the context for specific understanding.

[0174] In the present invention, "at least one" means one or more, and "more than one" means two or more. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can be represented by: a, b, c, ab, ac, bc, or abc, where a, b, c can be single or multiple.

[0175] It should be understood that in various embodiments of the present invention, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0176] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0177] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described equipment, devices and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0178] In the several embodiments provided by the present invention, it should be understood that the disclosed devices, apparatuses and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0179] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0180] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0181] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0182] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A clustered network topology agile discovery method based on battlefield roaming agents, characterized in that: The method comprises: S1. Obtain network topology information of a wireless ad hoc network to be discovered; S2, obtaining a network topology discovery result according to the roaming agents in the wireless self-organizing network and the hierarchical optimal search strategy of the roaming agents; S3. After a preset time interval, adjust the number of roaming agents according to the number of roaming agents and the network topology discovery quality evaluation mechanism; S4. According to the adjusted roaming agent and the hierarchical optimal search strategy of the roaming agent, an optimized network topology discovery result is obtained.

2. The clustered network topology agile discovery method based on battlefield roaming agents according to claim 1 is characterized in that: The wireless self-organizing network in S1 includes a plurality of nodes, and the plurality of nodes are divided into a plurality of clusters; For each of the plurality of clusters, a node is selected as a cluster head, and other nodes except the selected cluster head are cluster members; when the cluster head is selected, a roaming agent is generated; A gateway node is selected from the cluster heads or cluster members.

3. The clustered network topology agile discovery method based on battlefield roaming agents according to claim 2 is characterized in that: The step of selecting a gateway node from the cluster head or cluster members comprises: During the intra-cluster topology exchange, after the cluster members are initialized, they monitor the frequency hopping sequence to determine whether any cluster members have received the query information from the cluster head of other clusters; If so, the cluster member that receives the query information is a gateway node, and updates the neighbor cluster head table; If not, the cluster head is the gateway node; The gateway node feeds back topology information to the cluster head to which the gateway node belongs every preset intra-cluster response time interval; When exchanging topology between clusters, the gateway node exchanges topology information with the roaming agent and the neighboring cluster head; The gateway node also sends a flag bit to the cluster head to which the gateway node belongs, so as to ensure that the gateway node and the cluster head to which the gateway node belongs can continue to exchange topology information with the roaming agent when the connection is lost.

4. The clustered network topology agile discovery method based on battlefield roaming agents according to claim 1 is characterized in that: The hierarchical optimization search strategy of the roaming agent in S2 includes: The priority of the gateway node is defined as 1, and the priority of the cluster member is defined as 0. For any node a0, its neighbor node a i The distance between (i=1,2,…n) and node a0 is d i (i=1,2,…n), n represents the total number of nodes; If node a0's neighbor node a i If there is only one node with a priority of 1 and has not been traversed, then this node is selected as the next hop node; If node a0's neighbor node a i If there are multiple nodes with the same priority and have not been traversed, then select the node a with the smallest distance among the nodes with the same priority. j is the next hop node, (j=1,2,…n).

5. The clustered network topology agile discovery method based on battlefield roaming agents according to claim 1 is characterized in that: The network topology discovery quality evaluation mechanism includes: The path convergence of the wireless ad hoc network is calculated as shown in the following formula (1): In the formula, α represents the path convergence, ∑α p It represents the sum of the node pair connectivity obtained by all nodes in the wireless ad hoc network at a certain moment, and n represents the total number of nodes; Calculate the perception accuracy as shown in the following formula (2): In the formula, P represents the perception accuracy, and M0 represents the adjacency matrix of node m. Satisfied middle The number of P Represents the adjacency matrix of node m Satisfied middle The number of, M1 represents the actual adjacency matrix A(t) = (a pq ) n×n Satisfy a pq =1(p,q=1,2,…n) pq The number of P Represents the adjacency matrix of node m Satisfied middle the number of The available spectrum accuracy of all nodes in the network topology discovery process in the wireless ad hoc network is calculated as shown in the following formula (3): In the formula, γ represents the accuracy of available spectrum, ∑γ m It represents the sum of the available spectrum accuracy of all cognitive nodes at a certain moment obtained by the topology discovery process in the network.

6. The clustered network topology agile discovery method based on battlefield roaming agents according to claim 1 is characterized in that: The step S3, after a preset time interval, adjusting the number of roaming agents according to the number of roaming agents and a network topology discovery quality evaluation mechanism, includes: After the preset agent number self-check time interval, determine whether the number of roaming agents is less than the number of cluster heads. If so, generate a new roaming agent and copy the topology information; After a preset network performance evaluation time interval, determine whether the path convergence α is less than a preset path convergence threshold α min , or the perception accuracy P is less than the preset perception accuracy threshold P min , or the available spectrum accuracy γ is less than the preset spectrum accuracy threshold γ min , if so, a new roaming agent is generated and the topology information is copied.

7. A clustered network topology agile discovery device based on battlefield roaming agents, the clustered network topology agile discovery device based on battlefield roaming agents is used to implement the clustered network topology agile discovery method based on battlefield roaming agents as claimed in any one of claims 1 to 6, characterized in that: The device comprises: An acquisition module, used to acquire network topology information of a wireless self-organizing network to be discovered; A topology discovery module is used to obtain network topology discovery results based on roaming agents in the wireless self-organizing network and the hierarchical optimal search strategy of the roaming agents; An adjustment module, configured to adjust the number of roaming agents according to the number of roaming agents and a network topology discovery quality evaluation mechanism after a preset time interval; The output module is used to obtain an optimized network topology discovery result according to the adjusted roaming agent and the hierarchical optimal search strategy of the roaming agent.

8. The clustered network topology agile discovery device based on battlefield roaming agents according to claim 7 is characterized in that: The adjusting the number of roaming agents after a preset time interval according to the number of roaming agents and a network topology discovery quality evaluation mechanism includes: After the preset agent number self-check time interval, determine whether the number of roaming agents is less than the number of cluster heads. If so, generate a new roaming agent and copy the topology information; After a preset network performance evaluation time interval, determine whether the path convergence α is less than a preset path convergence threshold α min , or the perception accuracy P is less than the preset perception accuracy threshold P min , or the available spectrum accuracy γ is less than the preset spectrum accuracy threshold γ min , if so, a new roaming agent is generated and the topology information is copied.

9. A cluster network topology agile discovery device, characterized in that: The cluster network topology agile discovery device includes: processor; A memory having computer-readable instructions stored thereon, wherein when the computer-readable instructions are executed by the processor, the method according to any one of claims 1 to 6 is implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores program codes, which can be called by a processor to execute the method according to any one of claims 1 to 6.

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