CN114222309B - Multi-machine collaborative ad hoc network method based on consent theory - Google Patents
Multi-machine collaborative ad hoc network method based on consent theory Download PDFInfo
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Abstract
The application belongs to the technical field of command control, and particularly relates to a multi-machine collaborative self-networking method based on a consent theory. Comprising the following steps: step one, constructing a multi-machine cooperative networking consent relation diagram model based on a consent networking mechanism, which comprises the following steps: obtaining local communication requirements of each node for realizing overall efficiency of a network, and discretizing the local communication requirements; disassembling continuous multi-hop data information flow in a network into consent of discrete nodes to peripheral nodes of the discrete nodes, and publishing self intention to other nodes in a consent mode by the nodes and mutually meeting requirements to obtain a multi-machine cooperative networking consent relation diagram model; defining a promised redemption mechanism in the multi-machine cooperative networking promised relation graph model, wherein the promised redemption mechanism comprises the following steps: acquiring the value of promised behaviors among nodes, wherein the value is the service quality level corresponding to the promised behaviors; establishing a rewards and punishment mechanism for the bargained game based on the value of the consent act enables the consent to be redeemed.
Description
Technical Field
The application belongs to the technical field of command control, and particularly relates to a multi-machine collaborative self-networking method based on a consent theory.
Background
The multi-frame unmanned aerial vehicle/unmanned aerial vehicle collaborative execution task needs to carry out networking communication through a data chain, when facing a complex environment, isomorphic/heterogeneous platform nodes in the multi-machine collaborative data communication network can frequently carry out high-speed maneuver, meanwhile, the conditions of node damage, inter-node data link interruption and the like can be accompanied, the nodes can be randomly added or withdrawn, and inter-machine network topology separation and splitting are randomly and rapidly changed. Therefore, a multi-node mobile ad hoc network strategy needs to be designed, and a multi-hop off-center communication network with strong robustness needs to be established to meet the requirement of multi-machine collaborative interaction operation.
The existing mobile node ad hoc network strategy generally selects to actively maintain a routing path during the movement of the node or starts to passively perform routing discovery when the node needs to communicate, the implementation is based on the fact that any node can orderly operate according to a plan, when the node moves at a high speed and the topology changes severely, the adaptation capability to the state change of the peripheral node is lacking, a large amount of manual intervention configuration operation is needed, all data interaction of all communication nodes is difficult to manage and control through manual intervention, the node is difficult to be completely controlled by preset configuration, the robustness of the multi-machine collaborative network is poor, and dynamic autonomy and self-repair of the network are difficult to realize.
It is therefore desirable to have a solution that overcomes or at least alleviates at least one of the above-mentioned drawbacks of the prior art.
Disclosure of Invention
The present application aims to provide a multi-machine collaborative ad hoc network method based on a consent theory, so as to solve at least one problem existing in the prior art.
The technical scheme of the application is as follows:
a multi-machine collaborative self-networking method based on a consent theory comprises the following steps:
step one, constructing a multi-machine cooperative networking consent relation diagram model based on a consent networking mechanism, which comprises the following steps:
obtaining local communication requirements of each node for realizing overall efficiency of a network, and discretizing the local communication requirements;
disassembling continuous multi-hop data information flow in a network into consent of discrete nodes to peripheral nodes of the discrete nodes, and publishing self intention to other nodes in a consent mode by the nodes and mutually meeting requirements to obtain a multi-machine cooperative networking consent relation diagram model;
defining a promised redemption mechanism in the multi-machine cooperative networking promised relation graph model, wherein the promised redemption mechanism comprises the following steps:
acquiring the value of promised behaviors among nodes, wherein the value is the service quality level corresponding to the promised behaviors;
establishing a rewards and punishment mechanism for the bargained game based on the value of the consent act enables the consent to be redeemed.
In at least one embodiment of the present application, in the multimachine collaborative networking consent relationship graph model, the consent is defined as an autonomous statement of the behavior of an agent node, each basic consent includes a sending node S, a receiving node R, and a consent body pi, where the following formula indicates that the node S offers the subject b to the node R consent:
in at least one embodiment of the present application, the attribute sets of the sending node S and the receiving node R include a node type, a number ID of a node registered in a network, a specific capability of the node in the network, and a consent table established by the node according to its own functional requirements for other types of nodes:
S/R::[Type,ID,Capacity,table]。
in at least one embodiment of the present application, the consent body pi is a double combination (τ, χ), where τ is a consent type, χ is a constraint indicating a subset of possible values within the τ domain that proxy consent reserves, characterized by a binary relationship of the sending node S and the receiving node R:
in at least one embodiment of the present application, the subject b represents some constraint, matching behavior, event, or service.
In at least one embodiment of the present application, the consent types include use consent, conditional consent, and collaborative consent, where,
the use consent is in the form of:
representing that the sending node S promises to use the service b to the receiving node R;
the conditional consent is in the form of:
indicating that the sending node S promises to complete b1 service for the receiving node R under the condition of following event b 2;
the form of the collaboration consent is:
representing that the sending node S promises to do the same thing as the receiving node R on a class b event, involves the mutual compliance and imitation of the two nodes on the transmission of information.
In at least one embodiment of the present application, the rewards and punishment mechanism for establishing a bargained game based on the value of the consent act enables the consent to be redeemed includes:
based on the value of consent behavior, establishing iterative bargained gaming relationships between nodes, for mutually consent nodes A and B:
wherein v is value;
the evaluation of the quality of service level is accomplished by iterating the quality of service level provided by the gaming node at the previous time and the quality of service level provided at an earlier time:
v 1 (t+1)＝b 2 v 2 (t)v 2 (t-1)+a 2 v 2 (t)
v 2 (t+1)＝b 1 v 1 (t)v 1 (t-1)+a 1 v 1 (t)
through iterative comparison at different moments, the value change condition of promised behaviors is obtained, and a reward and punishment mechanism is established according to the value change condition:
when the value of the consent action is lower and lower, defining the consent action as a selfish node, punishing the selfish node, and reducing the consent credit of the selfish node;
and when the promised credit of the selfish node is reduced to a certain threshold value, promised following probability of other nodes to the selfish node is reduced, and network dynamic balance is realized.
In at least one embodiment of the present application, the method further includes a step three of calculating robustness of the multimachine cooperative networking consent relationship graph model:
representing any node in the multimachine collaborative networking consent relation graph model with other nodes by a set of reliability evaluation adjacency matrices:
the adjacency matrix is expressed as an n-order square matrix a formed by linear combination of the following formulas:
wherein n is the number of nodes in the multi-machine cooperative networking consent relation diagram model;
the non-promised relationship corresponds to a rank value of 0.
The invention has at least the following beneficial technical effects:
according to the multi-machine collaborative self-networking method based on the consent theory, the idea of carrying out forced constraint on communication relations among nodes is replaced by a mode of mutual consent among the nodes, a network which can still operate in an autonomous collaborative mode under the limitations of capacity, conditions, environment and the like is established, and the problem of poor robustness of the multi-machine collaborative self-networking under the high dynamic environment is solved.
Drawings
FIG. 1 is a flow chart of a multi-machine collaborative ad hoc networking method based on the consent theory according to one embodiment of the present application;
FIG. 2 is a schematic diagram of a task-oriented multi-machine collaborative networking consent relationship diagram model in accordance with one embodiment of the present application.
Detailed Description
In order to make the purposes, technical solutions and advantages of the implementation of the present application more clear, the technical solutions in the embodiments of the present application will be described in more detail below with reference to the accompanying drawings in the embodiments of the present application. In the drawings, the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The described embodiments are some, but not all, of the embodiments of the present application. The embodiments described below by referring to the drawings are exemplary and intended for the purpose of explaining the present application and are not to be construed as limiting the present application. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without making any inventive effort, are intended to be within the scope of the present application. Embodiments of the present application are described in detail below with reference to the accompanying drawings.
In the description of the present application, it should be understood that the terms "center," "longitudinal," "lateral," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," and the like indicate orientations or positional relationships based on the orientations or positional relationships illustrated in the drawings, merely to facilitate description of the present application and simplify the description, and do not indicate or imply that the device or element being referred to must have a specific orientation, be configured and operated in a specific orientation, and therefore should not be construed as limiting the scope of protection of the present application.
The present application is described in further detail below with reference to fig. 1-2.
The application provides a multi-machine collaborative self-networking method based on a consent theory, which comprises the following steps:
s100, constructing a multi-machine cooperative networking consent relation diagram model based on a consent networking mechanism, wherein the multi-machine cooperative networking consent relation diagram model comprises the following steps:
obtaining local communication requirements of all nodes for realizing overall efficiency of the network, and discretizing the local communication requirements;
disassembling continuous multi-hop data information flow in a network into consent of discrete nodes to peripheral nodes of the discrete nodes, and publishing self intention to other nodes in a consent mode by the nodes and mutually meeting requirements to obtain a multi-machine cooperative networking consent relation diagram model;
s200, defining a promised redemption mechanism in a multi-machine cooperative networking promised relation diagram model, wherein the promised redemption mechanism comprises the following steps:
acquiring the value of promised behaviors among nodes, wherein the value is the service quality level corresponding to the promised behaviors;
establishing a rewards and punishment mechanism for the bargained game based on the value of the consent act enables the consent to be redeemed.
According to the multi-machine cooperative self-networking method based on the consent theory, firstly, a multi-machine cooperative networking consent relation diagram model is built based on a consent networking mechanism. Consent between nodes is defined as a declarative statement of the desired behavior that the node is to perform, including the body, quality/quantity, trustworthiness, and other characteristics of the desired state. All independent autonomous nodes in the model can form expectations of mutual cooperative behavior through mutual consent, so that a complete end-to-end working system is built. If the mutual consent relation among the nodes can be established according to what information each node in the autonomous cooperative network expects to acquire from the network, the operation of all the nodes through manual intervention in a high dynamic environment can be reduced, the breakdown probability of the whole network when the network nodes cannot address logic according to a preset communication route is reduced, and the forced adherence of the nodes is changed into voluntary cooperation.
In the preferred embodiment of the present application, in the multimachine collaborative networking consent relationship graph model, consent is defined as an autonomous statement of the behavior of an agent node, each basic consent includes a sending node S, a receiving node R, and a consent body pi, and the following formula indicates that the node S provides the subject b to the node R consent:
the attribute sets of the sending node S and the receiving node R include node types, number IDs of the nodes registered in the network, specific capabilities of the nodes in the network, and consent tables (including available services and services to be accepted) of the nodes of other types established by the nodes according to their own functional requirements:
S/R::[Type,ID,Capacity,table]。
the consent body pi describes the consent topic b, specifying what is specifically promised, typically a double combination (τ, χ), where τ is the consent type and χ is a constraint indicating a subset of the possible values within τ that the agent promises to reserve, characterized by the binary relationship of the sending node S and the receiving node R:
the topic b represents some constraint, matching behavior, event or service.
According to the multi-machine collaborative self-networking method based on the consent theory, when a consent relation network is constructed, local communication requirements of each node for realizing overall network efficiency are firstly analyzed, a plurality of local requirements are discretized, continuous multi-hop data information flows in the network are disassembled into consent of discrete nodes to peripheral nodes, the nodes publish self intention to other nodes in a consent mode and mutually meet the requirements, and corresponding service contracts such as collaboration, use, conditions and the like are established according to the consent. And establishing a consent relation table for the peripheral nodes at each node, and considering that the communication between the two nodes meets the overall requirement when consent is complied with, and completing effective interaction of information between the nodes in a consent continuously-honoring mode.
In this embodiment, the promised types applied to the inter-node networking communication are designed as follows:
TABLE 1
The logic of the above process essentially transfers the overall desire or goal of the network global to a certain area or node in the network, and presets the behavior of all nodes as probabilistic properties of the agent according to the self intention, describing the overall operation logic of the network through discretized spontaneous consent of each node. Each node must achieve its own consent by using its forward consent to ensure that it adheres to dependencies in the network.
The system attributes of the consent network can be combined and analyzed by using a graphic language, the communication topological connection among the multiple nodes is abstracted into consent information flow, and then the consent relation diagram is obtained, wherein the consent relation diagram is equivalent to discretizing each node of the whole communication network, does not pay attention to the final addressing route target of a certain node, and only considers the communication consent made to the adjacent nodes.
And (3) providing a consent table for each class of nodes according to the communication requirements of the nodes, and immediately searching each object node according to the consent table and publishing own intention and address information to the object node after the nodes join in the network for registration. When the target adjacent node is damaged and exits the network, the source node searches the promised relation between the source node and other adjacent nodes which are established according to the same intention and are searched according to the promised table, address information and the like required by addressing transmission among the nodes are contained in promised main body information, and finally, the dynamic closed-loop operation of the whole network is realized.
In one embodiment of the application, for multi-machine cooperation, if an airplane is taken as a node as a whole, the amount of consent information required by the node is too large, so that discretization of functions of an airplane platform is considered to be carried out for a task, various computing devices, sensors and the like are taken as independent functional nodes to be embedded into a consent model,and a multi-machine cooperative networking consent relation diagram model of a certain task scene is established according to the theory, as shown in fig. 2. The model comprises a plurality of functional nodes, which are divided into detection O, attack F, interference S and command class nodes C, wherein T represents a target node. R represents the promise relationship between the nodes,
the command node C promises to issue a striking instruction to the striking node F, and F promises to execute the striking instruction after receiving and report the damage evaluation result to the command node C; />
The command node C promises to issue a detection instruction to the detection node O, and the detection instruction is executed and a detection result is reported back to the C after the O promises to receive the detection instruction; />
The command node C promises to issue an electronic interference instruction to the interference node S, and the S promises to execute electronic interference after receiving and report the load state to the C; r is R c Representing collaborative probing, hit consent relation (collaborative consent type) between nodes of the same type; />
Representing the promise of detecting, striking, and electronically interfering with a preset or on-demand target node.
The multi-machine cooperative self-networking method based on the consent theory needs to define a consent redemption mechanism in a multi-machine cooperative networking consent relation diagram model. Whether consent is honored is critical to the reliability of the networking, and there may be some selfish nodes in the consent network, in order to pursue the maximization of its "demand", some consent may not be honored in the absence of an effective node rewards and punishment strategy, and the lack of this part of data forwarding may result in other nodes consent not honored. Because each communication node in the network has no priori cooperative obligation, the corresponding prize and punish mechanism is established by adopting the method of the inter-node price negotiating game to realize autonomous cooperation, and consent is agreed to be honored and can be regarded as a steady-state balancing result after the inter-node game.
The precondition of bargained gaming between nodes is that the promised behavior has value, the probability of honoring the promised function is defined as the value of the promised behavior for the duration of promised to be followed, i.e., the quality of service and reliability provided during the service contract agreement period, and only the promised recipient can realize the value. The consent recipient may measure the value of the offered one or more consents in terms of perceived reliability. The value may motivate the nodes to adhere to redemption consent in the game, promoting reliability of the consent network.
In a preferred embodiment of the present application, establishing a prize mechanism for the bargained game based on the value of the consent act enables the consent to be redeemed including:
based on the value of consent behavior, establishing iterative bargained gaming relationships between nodes, for mutually consent nodes A and B:
wherein v is value;
the evaluation of the quality of service level is accomplished by iterating the quality of service level provided by the gaming node at the previous time and the quality of service level provided at an earlier time:
v 1 (t+1)＝b 2 v 2 (t)v 2 (t-1)+a 2 v 2 (t)
v 2 (t+1)＝b 1 v 1 (t)v 1 (t-1)+a 1 v 1 (t)
through iterative comparison at different moments, the value change condition of promised behaviors is obtained, and a reward and punishment mechanism is established according to the value change condition:
when the value of the consent action is lower and lower, defining the consent action as a selfish node, punishing the selfish node, and reducing the consent credit of the selfish node;
and when the promised credit of the selfish node is reduced to a certain threshold value, promised following probability of other nodes to the selfish node is reduced, and network dynamic balance is realized.
In this embodiment, if the node B promises to forward the message of the neighboring node a to the neighboring node C, the message sent by the neighboring node C may be cached, and if the message is consistent with the cache, the forwarding may be completed by monitoring the forwarding content of the node B, and if the message is consistent with the cache, the node B may instruct the forwarding, and by performing iterative comparison at different moments, determine the quality change condition of the service level of the promised behavior, and establish a reward mechanism according to the value change condition, and when the value of the promised behavior is lower, instruct the node B not to adhere to the promised behavior, define the promised behavior as a selfish node, and perform corresponding punishment on the selfish node, thereby reducing the promised reputation. For promised network each intelligent node is configured as a dynamic adjusting module which gradually tends to increase promised credit, if the promised credit of source node is reduced to a certain threshold value, the adjacent node will also reduce promised following probability to the source node, and finally network dynamic balance is realized.
Further, the multi-machine cooperative self-networking method based on the consent theory comprises S300, calculating robustness of a multi-machine cooperative networking consent relation diagram model.
A method of quantitatively calculating the probability that a consent is complied with in a network may be established based on graph theory, where consent of a source node has a certain continuity characteristic, and where the consent's function affects other nodes probabilistically along each link in the network. Any node in the consent network can represent the relation with other nodes through a group of adjacency matrixes, if an iterative game linear calculation relation for consent service level evaluation among adjacent nodes is established, the linear calculation relations are integrated to form a reliability evaluation adjacency matrix, and the overall judgment basis of the reliability of the consent network can be obtained from the view of graph theory, so that the network robustness criterion under the conditions of node damage and the like is obtained.
In this embodiment, any node in the multi-machine cooperative networking consent relationship graph model represents a relationship with other nodes through a set of reliability evaluation adjacency matrices:
the adjacency matrix is expressed as an n-order square matrix a formed by linear combination of the following formulas:
wherein n is the number of nodes in the multi-machine cooperative networking consent relation diagram model;
the non-promised relationship corresponds to a rank value of 0.
The larger the matrix eigenvalue, the more robust.
According to the multi-machine collaborative self-networking method based on the consent theory, each dynamic communication node in the multi-machine collaborative network is considered as an intelligent individual (Agent), the requirements for communication content and routing addressing paths of the dynamic communication nodes are not forcedly issued to each node, service contracts are formed through mutual consent among the nodes, excessive manual intervention configuration is not needed in a high dynamic environment, and the self-organizing network of supporting node joining and exiting along with meeting is realized.
The multi-machine cooperative self-networking method based on the consent theory, which is disclosed by the application, is used for conceiving a new idea of realizing multi-node dynamic networking based on mutual consent, and compared with the existing dynamic self-networking method, all communication multi-hop paths of all nodes in a network are prevented from being defined and managed in a centralized manner, each node is promised with adjacent nodes according to own needs to form a service contract, and a reward and punishment mechanism of bargained game is established, so that consent can be honored, dynamic balance is realized, and finally, a strong-robustness autonomous cooperative network is constructed. Besides multi-machine cooperation, the method can be further expanded to other application scenes such as unmanned vehicles and the like needing dynamic networking communication.
The foregoing is merely specific embodiments of the present application, but the scope of the present application is not limited thereto, and any changes or substitutions easily conceivable by those skilled in the art within the technical scope of the present application should be covered in the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (8)
1. The multi-machine cooperative ad hoc network method based on the consent theory is characterized by comprising the following steps of:
step one, constructing a multi-machine cooperative networking consent relation diagram model based on a consent networking mechanism, which comprises the following steps:
obtaining local communication requirements of each node for realizing overall efficiency of a network, and discretizing the local communication requirements;
disassembling continuous multi-hop data information flow in a network into consent of discrete nodes to peripheral nodes of the discrete nodes, and publishing self intention to other nodes in a consent mode by the nodes and mutually meeting requirements to obtain a multi-machine cooperative networking consent relation diagram model;
defining a promised redemption mechanism in the multi-machine cooperative networking promised relation graph model, wherein the promised redemption mechanism comprises the following steps:
acquiring the value of promised behaviors among nodes, wherein the value is the service quality level corresponding to the promised behaviors;
establishing a rewards and punishment mechanism for the bargained game based on the value of the consent act enables the consent to be redeemed.
2. The method of claim 1, wherein in the model of a multi-machine collaborative networking consent relationship, the consent is defined as an autonomous statement of the behavior of an agent node, each basic consent comprises a sending node S, a receiving node R, and a consent body pi, and the following formula indicates that the node S promises provides the subject b to the node R:
3. the method according to claim 2, wherein the attribute sets of the sending node S and the receiving node R include node types, number IDs of nodes registered in the network, specific capabilities of nodes in the network, and consent tables established by the nodes according to their own function requirements for other types of nodes:
S/R::[Type,ID,Capacity,table]。
4. the method of claim 3, wherein the consent body pi is a double combination (τ, χ), where τ is a consent type, χ is a constraint, indicating a subset of possible values within τ -domain that are held by agent consent, characterized by a binary relationship of the sending node S and the receiving node R:
5. the method of consent theory based multimachine collaborative ad hoc networking according to claim 4, wherein the topic b represents a constraint, matching behavior, event or service.
6. The method of claim 5, wherein the consent types include use consent, conditional consent, and collaborative consent, wherein,
the use consent is in the form of:
representing that the sending node S promises to use the service b to the receiving node R;
the conditional consent is in the form of:
indicating that the sending node S promises to complete b1 service for the receiving node R under the condition of following event b 2;
the form of the collaboration consent is:
representing that the sending node S promises to do the same thing as the receiving node R on a class b event, involves the mutual compliance and imitation of the two nodes on the transmission of information.
7. The consent theory-based multi-machine collaborative ad hoc networking method according to claim 6, wherein the consent-action-based value-building bargained game prizes and punishments mechanism enables consent redemption comprising:
based on the value of consent behavior, establishing iterative bargained gaming relationships between nodes, for mutually consent nodes A and B:
wherein v is value;
the evaluation of the quality of service level is accomplished by iterating the quality of service level provided by the gaming node at the previous time and the quality of service level provided at an earlier time:
v 1 (t+1)＝b 2 v 2 (t)v 2 (t-1)+a 2 v 2 (t)
v 2 (t+1)＝b 1 v 1 (t)v 1 (t-1)+a 1 v 1 (t)
through iterative comparison at different moments, the value change condition of promised behaviors is obtained, and a reward and punishment mechanism is established according to the value change condition:
when the value of the consent action is lower and lower, defining the consent action as a selfish node, punishing the selfish node, and reducing the consent credit of the selfish node;
and when the promised credit of the selfish node is reduced to a certain threshold value, promised following probability of other nodes to the selfish node is reduced, and network dynamic balance is realized.
8. The method of multi-machine collaborative ad hoc networking based on the consent theory according to claim 7, further comprising the step of calculating the robustness of the multi-machine collaborative networking consent relationship graph model:
representing any node in the multimachine collaborative networking consent relation graph model with other nodes by a set of reliability evaluation adjacency matrices:
the adjacency matrix is expressed as an n-order square matrix a formed by linear combination of the following formulas:
wherein n is the number of nodes in the multi-machine cooperative networking consent relation diagram model;
the non-promised relationship corresponds to a rank value of 0.
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| CN103152788A (en) * | 2013-02-21 | 2013-06-12 | 湖南大学 | Game-based VMIMO (Virtual Multiple Input Multiple Output) cooperative routing method |
| CN113613257A (en) * | 2021-07-16 | 2021-11-05 | 中国空间技术研究院 | Game theory-based sensor network self-organizing cooperative k covering method |
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| CN103152788A (en) * | 2013-02-21 | 2013-06-12 | 湖南大学 | Game-based VMIMO (Virtual Multiple Input Multiple Output) cooperative routing method |
| CN113613257A (en) * | 2021-07-16 | 2021-11-05 | 中国空间技术研究院 | Game theory-based sensor network self-organizing cooperative k covering method |
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| A Promise Theory Approach to Understanding Resilience: Faults, Errors, and Tolerance within Systems;Mark Burgess;《ResearchGate》;全文 * |
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