A complex network performance evaluation method and device

Abstract

The application discloses a complex network performance evaluation method and device, the method comprises the following steps: constructing a complex network structure diagram of a combat system; constructing a whole-stage information node relationship network model based on a process perspective and one or more sub-stage information node relationship network models based on an object perspective according to the complex network structure diagram; performing performance evaluation on the whole-stage information node relationship network model and each sub-stage information node relationship network model respectively, wherein indexes used in the performance evaluation include the shortest link completion time, the shortest link resource consumption and the shortest link completion probability; and obtaining the performance evaluation result of the combat system according to the performance evaluation results of the whole-stage information node relationship network model and each sub-stage information node relationship network model. Since the information based on the process perspective and the information based on the object perspective are combined, the accuracy of the evaluation result is higher, and the performance evaluation problem of the complex network can be effectively solved.

Description

Technical Field

[0001] This invention belongs to the field of system performance evaluation technology, specifically relating to a method and apparatus for evaluating the performance of complex networks. Background Technology

[0002] The application of information technology and other advanced military technologies has drastically changed the nature of warfare, shifting the emphasis from the performance of individual equipment to the coordinated operations and cooperation among various weapon systems. In actual combat, the interconnectedness and coupling between weapons and equipment are becoming increasingly strong, resulting in a large amount of dynamic information exchange. Therefore, when evaluating the effectiveness of a combat system, it is necessary to consider the interactive influences between equipment.

[0003] The foundation of combat system evaluation is system modeling. One of the current mainstream methods is the network-based approach, which abstracts equipment entities as network nodes and the relationships between equipment as edges in the network. It has unique advantages in describing the relationships between equipment, can reflect the network characteristics of complex systems, and has been widely recognized and accepted.

[0004] With the continuous development of information systems and the expansion of single network links, the complexity of complex networks has increased significantly due to the expansion of nodes. Currently, in the field of combat system effectiveness evaluation, the measurement of the effectiveness of complex networks is mainly based on the kill chain evaluation method. This method analyzes the characteristics and correlations of each node based on a large number of information nodes and link structures. However, when the number of kill chains is small and the link structure cannot be expanded, it becomes difficult to deeply explore the weak links and their causes. Furthermore, analysis based on a single link results in a lack of overall network analysis.

[0005] There is currently no solution to the problem that existing methods for measuring the performance of complex networks in information systems cannot function properly for systems with complex structures and large scales. Summary of the Invention

[0006] This invention provides a method and apparatus for evaluating the performance of complex networks, which solves the problem that existing performance evaluation methods cannot properly evaluate the performance of systems with complex structures and large scale.

[0007] The first aspect of this invention discloses a method for evaluating the performance of complex networks, comprising:

[0008] Constructing a complex network structure diagram of the combat system;

[0009] Based on the complex network structure diagram, construct a full-stage information node relationship network model based on a process perspective and one or more sub-stage information node relationship network models based on an object perspective.

[0010] The performance of the full-stage information node relationship network model and each of the sub-stage information node relationship network models is evaluated. The performance evaluation indicators include the completion time of the shortest link, the resource consumption of the shortest link, and the completion probability of the shortest link.

[0011] Based on the effectiveness evaluation results of the full-stage information node relationship network model and each of the sub-stage information node relationship network models, the effectiveness evaluation results of the combat system are obtained.

[0012] Preferably, based on the complex network structure diagram, a full-stage information node relationship network model based on a process perspective and one or more sub-stage information node relationship network models based on an object perspective are constructed, specifically including:

[0013] The complex network structure is denoted as a full-stage information node relationship network model based on a process perspective;

[0014] Acquire one or more preset target information nodes;

[0015] From the complex network structure diagram, obtain the information network related to the target information node to obtain one or more sub-stage information node relationship network models based on the object perspective.

[0016] Preferably, the performance of the full-stage information node relationship network model and each of the sub-stage information node relationship network models is evaluated, specifically including:

[0017] Obtain the source node and sink node in the full-stage information node relationship network model and each sub-stage information node relationship network model;

[0018] Based on the source node and the sink node, determine the shortest link in the full-stage information node relationship network model and each sub-stage information node relationship network model;

[0019] The performance of the full-stage information node relationship network model and each of the sub-stage information node relationship network models is evaluated based on the completion time of the shortest link, the resource consumption of the shortest link, and the completion probability of the shortest link.

[0020] Preferably, the completion time of the shortest link is determined according to a first formula, which is:

[0021]

[0022] In the formula, The shortest link between source node a and sink node b. `act` represents the completion time of the shortest link, `act` is a multi-attribute tuple for each information node involved in the shortest link, and `act.delaytime` is the average delay time when the information node is executed.

[0023] Preferably, the resource consumption of the shortest link is determined according to a second formula, which is:

[0024]

[0025] In the formula, The shortest link between source node a and sink node b. The resource consumption of the shortest link is represented by `act`, which is a multi-attribute tuple for each information node involved in the shortest link, and `act.rc` is the average unit resource consumed when the information node is executed.

[0026] Preferably, the completion probability of the shortest link is determined according to a third formula, which is:

[0027]

[0028] In the formula, The shortest link between source node a and sink node b. is the completion probability of the shortest link, act is a multi-attribute tuple for each information node involved in the shortest link, and act.sp is the probability of successful information instruction processing.

[0029] Preferably, the performance of the full-stage information node relationship network model and each sub-stage information node relationship network model is evaluated based on the completion time of the shortest link, the resource consumption of the shortest link, and the completion probability of the shortest link, specifically including:

[0030] The performance of the full-stage information node relationship network model and each of the sub-stage information node relationship network models is evaluated according to the fourth formula, which is:

[0031] M=α1molp1+α2molp2+α3molp3

[0032] In the formula, M is the performance evaluation result, molp1 is the completion time of the shortest link, molp2 is the resource consumption of the shortest link, molp3 is the completion probability of the shortest link, α1, α2 and α3 are weights, and α1+α2+α3=1.

[0033] Preferably, the effectiveness evaluation result of the combat system is obtained based on the effectiveness evaluation results of the full-stage information node relationship network model and the information node relationship network model of each sub-stage, specifically including:

[0034] The effectiveness assessment result of the combat system is determined according to the fifth formula, which is:

[0035]

[0036] In the formula, E represents the effectiveness evaluation result of the combat system, and M... T and β T These are the performance evaluation results and weights of the full-stage information node relationship network model, M. Si and β Si These represent the performance evaluation results and weights of the information node relationship network model for the i-th sub-stage. Q represents the total number of sub-stage information node relationship network models.

[0037] Preferably, the attributes in the multi-attribute tuple include the information node name, the unique identifier of the information node, the type of the information node, the average latency time when the information node is executed, the average unit resource consumed when the information node is executed, and the probability of successful processing of the information instruction.

[0038] A second aspect of this invention discloses a complex network performance evaluation device, comprising:

[0039] Graph construction module, which is used to construct a complex network structure graph of the combat system;

[0040] The model building module is used to build a full-stage information node relationship network model based on the process perspective and one or more sub-stage information node relationship network models based on the object perspective, according to the complex network structure diagram.

[0041] The first evaluation module is used to evaluate the performance of the full-stage information node relationship network model and each of the sub-stage information node relationship network models. The performance evaluation indicators include the completion time of the shortest link, the resource consumption of the shortest link, and the completion probability of the shortest link.

[0042] The second evaluation module is used to obtain the effectiveness evaluation result of the combat system based on the effectiveness evaluation results of the full-stage information node relationship network model and each sub-stage information node relationship network model.

[0043] Compared with the prior art, the present invention has the following advantages:

[0044] This invention combines the effectiveness evaluation results of the full-stage information node relationship network model and the information node relationship network model of each sub-stage to calculate the effectiveness evaluation results of the combat system. Because it combines information based on the process perspective and information based on the object perspective, the evaluation results are more accurate and can effectively solve the effectiveness evaluation problem of complex networks. Attached Figure Description

[0045] Figure 1 This is a flowchart of a complex network performance evaluation method according to an embodiment of the present invention;

[0046] Figure 2 This is a schematic diagram of the structure of a complex network performance evaluation device according to an embodiment of the present invention.

[0047] In the diagram, 101 is the graph construction module; 102 is the model construction module; 103 is the first evaluation module; and 104 is the second evaluation module. Detailed Implementation

[0048] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the following embodiments are merely illustrative and explanatory of the present invention and should not be construed as limiting the scope of protection of the present invention. All technologies implemented based on the above content of the present invention are covered within the scope of protection intended by the present invention.

[0049] like Figure 1 As shown, the first aspect of the present invention discloses a method for evaluating the performance of complex networks, comprising:

[0050] Step 1: Construct a complex network structure diagram of the combat system.

[0051] Before constructing a complex network structure diagram of the combat system, it is necessary to first obtain the equipment in the combat system and the links between the equipment.

[0052] Then, construct a spatial swimlane activity diagram and a complex network structure diagram of the combat system.

[0053] When using a swimlane-based action diagram model to describe the combat process, removing the swimlanes (or adding the organizations and nodes corresponding to the swimlanes to the action / action attributes) will yield a complex network structure diagram, which is an information node relationship network model based on a process perspective.

[0054] When using the hierarchical IDEF0 method to describe the information sharing process, a method that removes the hierarchy can be used to establish a network model that retains only the sub-actions and their input-output relationships, which is the information node relationship network.

[0055] In this embodiment of the invention, the equipment of the combat system includes reconnaissance equipment, strike equipment, decision-making equipment, and target acquisition equipment. Each piece of equipment is abstracted as a node in a complex network structure, and the link relationships between different equipment nodes are analyzed, i.e., combat activities. Combat activities are treated as edges in the complex network structure. Specifically, combat activities include intelligence gathering activities, information transmission activities, coordination activities, and strike activities. Then, a complex network structure diagram of the combat system is constructed based on the nodes and their link relationships.

[0056] Step 2: Based on the complex network structure diagram, construct a full-stage information node relationship network model from a process perspective and one or more sub-stage information node relationship network models from an object perspective, specifically including:

[0057] Step 21: Describe the complex network structure diagram as a process-oriented, full-stage information node relationship network model.

[0058] Step 22: Obtain one or more preset target information nodes.

[0059] In this invention, the preset target information node can be any of the following: reconnaissance equipment, strike equipment, decision-making equipment, and target equipment.

[0060] Step 23: Obtain the information network related to the target information node from the complex network structure diagram to obtain one or more sub-stage information node relationship network models based on the object perspective.

[0061] A complex network refers to a network of relationships formed by the flow of various information (information status, processing commands, allocation instructions, information states, etc.) between nodes in an information system. From a process perspective, information is generated by one node and then flows to other nodes for use; information exists between nodes. A node, viewed on a larger scale, can be a workstation, server, or other connected device; viewed on a smaller scale, it can be a computer or terminal device. From an object perspective, each node necessarily has an executing entity. These entities can be people, organizations, etc., abstract entities or objects, collectively referred to as information nodes in system architecture modeling. Therefore, a system information network based on perspective analysis is a network formed by the information exchange relationships between nodes.

[0062] Complex operational network models describe the generation, processing, distribution, and use of various information during combat. A process-oriented, full-stage information node relationship network model retains more information about the information lifecycle, supporting the analysis of issues such as information link length and link completion probability. An object-oriented, sub-stage information node relationship network model focuses on describing the information exchange relationships between the entities that generate, process, and use the information, making it more suitable for analyzing the amount of information generated or used by each entity and the consumption of link resources.

[0063] Let the complex network structure be G = (V, E), where V = {act_i, i = 1, 2, ..., N_act} is the set of combat actions. Each information node `act` is a multi-attribute tuple, denoted as `act = (name, id, type, delaytime, rc, sp, peformer)`, where `name` represents the information node name, `id` is the unique identifier of the information node, `type` represents the type of the information node, `delaytime` is the average delay time when the information node executes, `rc` is the average unit resource consumed when the information node executes, `sp` is the probability of successful information command processing (0 ≤ sp ≤ 1), and `peformer` is the information node that processes information. Information node attributes can usually be accessed using `act.prop`, such as `act.name` returning the information node name. `type` takes values ​​from the set {O, P, D, A, S}, where O represents an information reconnaissance action, P represents an information processing action, D represents an information decision-making action, A represents an information transmission or feedback action, and S represents an information node maintenance action. When peformer is an information node, it also has a type, usually denoted as peformer.type, with values ​​{Ob,C2,Ac,Sm}, representing peformer information detection node, information decision-making node, information transmission node, and information node maintenance node, respectively.

[0064] E = {edge_j, j = 1, 2, ..., N_E} is the set of directed edges in a complex network structure. edge ∈ E is also a multi-attribute tuple, denoted as edge = (name, fromact, toact, infotype), where name is the name, fromact is the action at the beginning of the edge, toact is the action at the end of the edge, and infotype is the type of information flowing along the edge, taking values ​​from the set {intl, c2, st, null}, corresponding to four cases: situational information, command-based control information, state information, and no information.

[0065] Step 3: Conduct performance evaluations on the information node relationship network model for the entire stage and the information node relationship network model for each sub-stage. The performance evaluation indicators include the completion time of the shortest link, the resource consumption of the shortest link, and the completion probability of the shortest link, specifically including:

[0066] Step 31: Obtain the source and sink nodes in the full-stage information node relationship network model and the information node relationship network model of each sub-stage.

[0067] Step 32: Based on the source node and sink node, determine the shortest link in the full-stage information node relationship network model and the information node relationship network model of each sub-stage.

[0068] This invention uses a process-oriented, full-stage information node relationship network model as an example to illustrate a method for determining the shortest link between source nodes and sink nodes.

[0069] The functional links from a process perspective are generated based on an information node relationship network. Specifically, this involves removing edges with null information types from the information node relationship network, as well as the isolated combat operations resulting from them. The remaining subnet constitutes the system information network from a process perspective, denoted as the process-based full-stage information node relationship network model. Specifically: in:

[0070] satisfy edge.infotype = intl;

[0071]

[0072] Determine all source nodes (i.e. nodes with an in-degree of 0) in G_I=(V_I,E_I), denoted as V_(I,S);

[0073] Determine all sink nodes (i.e. nodes with an out-degree of 0) in G_I=(V_I,E_I), denoted as V_(I,T);

[0074] Let the shortest path in G_I = (V_I, E_I) with starting point a and ending point b be . but This is the shortest link.

[0075] Step 33: Evaluate the performance of the full-stage information node relationship network model and the information node relationship network model for each sub-stage based on the completion time of the shortest link, the resource consumption of the shortest link, and the completion probability of the shortest link.

[0076] The completion time of the shortest link is defined as the time taken from the start to the end of the link, that is, the sum of the execution time of the entire operational operation along the link. This is determined according to the first formula, which is:

[0077]

[0078] In the formula, The shortest link between source node a and sink node b. `act` represents the completion time of the shortest link, `act` is a multi-attribute tuple for each information node involved in the shortest link, and `act.delaytime` is the average delay time when the information node is executed.

[0079] The resource consumption of the shortest link is defined as the sum of resources consumed in the link's operational activities, determined according to the second formula, which is:

[0080]

[0081] In the formula, The shortest link between source node a and sink node b. The resource consumption of the shortest link is represented by `act`, which is a multi-attribute tuple for each information node involved in the shortest link, and `act.rc` is the average unit resource consumed when the information node is executed.

[0082] The probability of completing the shortest link is defined as the product of the probabilities of completing the link-based combat operation, determined according to the third formula, which is:

[0083]

[0084] In the formula, The shortest link between source node a and sink node b. is the completion probability of the shortest link, act is a multi-attribute tuple for each information node involved in the shortest link, and act.sp is the probability of successful information instruction processing.

[0085] The attributes in the above-mentioned act multi-attribute tuple include the information node name, the unique identifier of the information node, the type of the information node, the average latency time when the information node is executed, the average unit resource consumed when the information node is executed, and the probability of successful processing of information instructions.

[0086] Then, the performance of the full-stage information node relationship network model and the information node relationship network model for each sub-stage is evaluated based on the completion time, resource consumption, and completion probability of the shortest link. Specifically, this includes:

[0087] The effectiveness of the full-stage information node relationship network model and the information node relationship network model for each sub-stage is evaluated based on the fourth formula, which is:

[0088] M=α1molp1+α2molp2+α3molp3

[0089] In the formula, M is the performance evaluation result, molp1 is the completion time of the shortest link, molp2 is the resource consumption of the shortest link, molp3 is the completion probability of the shortest link, α1, α2 and α3 are weights, and α1+α2+α3=1.

[0090] Step 4: Based on the effectiveness evaluation results of the full-stage information node relationship network model and the information node relationship network model for each sub-stage, obtain the effectiveness evaluation results of the combat system, specifically including:

[0091] The effectiveness assessment results of the combat system are determined based on the fifth formula, which is:

[0092]

[0093] In the formula, E represents the effectiveness assessment result of the combat system, and M... T and β T These are the performance evaluation results and weights of the full-stage information node relationship network model, M. Si and β Si These represent the performance evaluation results and weights of the information node relationship network model for the i-th sub-stage. Q represents the total number of sub-stage information node relationship network models.

[0094] The second aspect of this invention discloses a complex network performance evaluation device, such as... Figure 2 As shown, it includes a graph construction module 101, a model construction module 102, a first evaluation module 103, and a second evaluation module 104.

[0095] The graph construction module 101 is used to construct a complex network structure diagram of the combat system;

[0096] The model building module 102 is used to build a full-stage information node relationship network model based on the process perspective and one or more sub-stage information node relationship network models based on the object perspective, according to the complex network structure diagram.

[0097] The first evaluation module 103 is used to evaluate the performance of the information node relationship network model of the whole stage and the information node relationship network model of each sub-stage. The indicators used for performance evaluation include the completion time of the shortest link, the resource consumption of the shortest link, and the completion probability of the shortest link.

[0098] The second evaluation module 104 is used to obtain the effectiveness evaluation results of the combat system based on the effectiveness evaluation results of the full-stage information node relationship network model and the information node relationship network model of each sub-stage.

[0099] This invention combines the effectiveness evaluation results of the full-stage information node relationship network model and the information node relationship network model of each sub-stage to calculate the effectiveness evaluation results of the combat system. Because it combines information based on the process perspective and information based on the object perspective, the evaluation results are more accurate and can effectively solve the effectiveness evaluation problem of complex networks.

[0100] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the invention. Any person skilled in the art can make many possible variations and modifications to the technical solutions of the present invention, or modify them into equivalent embodiments, without departing from the scope of the present invention. Therefore, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention, without departing from the content of the present invention, should fall within the protection scope of the present invention.

Claims

1. A method for evaluating the performance of complex networks, characterized in that, include: Constructing a complex network structure diagram of the combat system; Based on the complex network structure diagram, construct a full-stage information node relationship network model based on a process perspective and one or more sub-stage information node relationship network models based on an object perspective. The performance of the full-stage information node relationship network model and each of the sub-stage information node relationship network models is evaluated. The performance evaluation indicators include the completion time of the shortest link, the resource consumption of the shortest link, and the completion probability of the shortest link. Based on the effectiveness evaluation results of the full-stage information node relationship network model and each of the sub-stage information node relationship network models, the effectiveness evaluation results of the combat system are obtained. The performance of the full-stage information node relationship network model and each of the sub-stage information node relationship network models is evaluated, specifically including: Obtain the source nodes and sink nodes in the full-stage information node relationship network model and each sub-stage information node relationship network model; Based on the source node and the sink node, determine the shortest link in the full-stage information node relationship network model and each sub-stage information node relationship network model; The performance of the full-stage information node relationship network model and each of the sub-stage information node relationship network models is evaluated based on the completion time of the shortest link, the resource consumption of the shortest link, and the completion probability of the shortest link.

2. The method as described in claim 1, characterized in that, Based on the complex network structure diagram, a full-stage information node relationship network model based on a process perspective and one or more sub-stage information node relationship network models based on an object perspective are constructed, specifically including: The complex network structure is denoted as a full-stage information node relationship network model based on a process perspective; Acquire one or more preset target information nodes; From the complex network structure diagram, obtain the information network related to the target information node to obtain one or more sub-stage information node relationship network models based on the object perspective.

3. The method as described in claim 1, characterized in that, The completion time of the shortest link is determined according to a first formula, which is: In the formula, For the source node a Hehui Node b The shortest link between them, Let be the completion time of the shortest link, and 'act' be a multi-attribute tuple for each information node involved in the shortest link. This represents the average latency time during the execution of information nodes.

4. The method as described in claim 1, characterized in that, The resource consumption of the shortest link is determined according to the second formula, which is: In the formula, For the source node a Hehui Node b The shortest link between them, The resource consumption of the shortest link is represented by `act`, which is a multi-attribute tuple for each information node involved in the shortest link. This represents the average unit resource consumed during the execution of an information node.

5. The method as described in claim 1, characterized in that, The completion probability of the shortest link is determined according to a third formula, which is: In the formula, Source node a Hehui Node b The shortest link between them, Let be the probability of completing the shortest link, and 'act' be a multi-attribute tuple for each information node involved in the shortest link. The probability of successfully processing an information instruction.

6. The method as described in claim 1, characterized in that, The performance of the full-stage information node relationship network model and each sub-stage information node relationship network model is evaluated based on the completion time of the shortest link, the resource consumption of the shortest link, and the completion probability of the shortest link. Specifically, this includes: The performance of the full-stage information node relationship network model and each of the sub-stage information node relationship network models is evaluated according to the fourth formula, which is: In the formula, For the performance evaluation results, The completion time of the shortest link. The resource consumption for the shortest link. This represents the probability of completing the shortest link. , and As weight, and .

7. The method according to any one of claims 1-6, characterized in that, Based on the effectiveness evaluation results of the full-stage information node relationship network model and each sub-stage information node relationship network model, the effectiveness evaluation results of the combat system are obtained, specifically including: The effectiveness assessment result of the combat system is determined according to the fifth formula, which is: In the formula, The effectiveness evaluation results of the aforementioned combat system. and These represent the performance evaluation results and weights of the full-stage information node relationship network model, respectively. and The first i Performance evaluation results and weights of the information node relationship network model in each sub-stage. , This represents the total number of information node relationship network models in the sub-stages.

8. The method according to any one of claims 3-5, characterized in that, The attributes in the multi-attribute tuple include the information node name, the unique identifier of the information node, the type of the information node, the average delay time when the information node is executed, the average unit resource consumed when the information node is executed, and the probability of successful processing of the information instruction.

9. A complex network performance evaluation device based on the method of any one of claims 1-8, characterized in that, include: Graph construction module, which is used to construct a complex network structure graph of the combat system; The model building module is used to build a full-stage information node relationship network model based on the process perspective and one or more sub-stage information node relationship network models based on the object perspective, according to the complex network structure diagram. The first evaluation module is used to evaluate the performance of the full-stage information node relationship network model and each of the sub-stage information node relationship network models. The performance evaluation indicators include the completion time of the shortest link, the resource consumption of the shortest link, and the completion probability of the shortest link, specifically including: Obtain the source nodes and sink nodes in the full-stage information node relationship network model and each sub-stage information node relationship network model; Based on the source node and the sink node, determine the shortest link in the full-stage information node relationship network model and each sub-stage information node relationship network model; The performance of the full-stage information node relationship network model and each of the sub-stage information node relationship network models is evaluated based on the completion time of the shortest link, the resource consumption of the shortest link, and the completion probability of the shortest link. The second evaluation module is used to obtain the effectiveness evaluation result of the combat system based on the effectiveness evaluation results of the full-stage information node relationship network model and each sub-stage information node relationship network model.

Images