Directional neighbor discovery method, device and electronic device based on asynchronous scanning

Abstract

The present invention provides a method, device and electronic device for directional neighbor discovery based on asynchronous scanning, which belongs to the field of communication technology, and includes: obtaining node cluster neighbor information; inputting the node cluster neighbor information into an objective function, iteratively calculating the optimal solution of the objective function based on constraint conditions, and obtaining target configuration parameters corresponding to the optimal solution, wherein the target configuration parameters include the sector selection strategy and listening time strategy of each node in the node cluster, and the objective function is used to minimize the average neighbor discovery time of the neighbor discovery process, or minimize the average energy consumption of the neighbor discovery process; controlling the node cluster to perform neighbor discovery based on the target configuration parameters. The directional neighbor discovery method based on asynchronous scanning provided by the present invention solves the technical problems of the directional neighbor discovery method based on asynchronous scanning in the related art, which has the delay and high energy consumption of the node cluster in the neighbor discovery process.

Description

Technical Field

[0001] The present invention relates to the field of communication technology, and in particular to a directional neighbor discovery method, device and electronic device based on asynchronous scanning. Background Art

[0002] The application of directional antenna technology in communication systems is becoming more and more extensive. Directional antenna technology uses different angles of space and the diversity of channels to improve the reliability, throughput and energy efficiency of communication. It is suitable for drone clusters, mobile communications and Internet of Things systems; neighbor discovery refers to the process of nodes identifying other communicative nodes around them by broadcasting and receiving signals. This process is the basis of many network protocols and applications, especially in drone clusters, wireless sensor networks and Internet of Things systems. The efficiency of neighbor discovery directly affects the overall performance of the network.

[0003] In asynchronous directional antenna systems, due to the inconsistent clocks between nodes, the traditional omnidirectional antenna neighbor discovery method is difficult to give full play to the advantages of directional antennas. In order to adapt to the asynchronous environment, existing technologies mostly rely on designing some scanning strategies, trying to improve the success rate of neighbor discovery by increasing the probability of scanning results. However, this method is not efficient in directional antenna systems, especially in asynchronous systems. Nodes cannot predict the communication status of neighbor nodes, resulting in a significant increase in delays and energy consumption in the discovery process.

[0004] It can be seen that the directional neighbor discovery method based on asynchronous scanning in the related art has technical problems such as delay and high energy consumption of the node cluster during the neighbor discovery process. Summary of the invention

[0005] The present invention provides a directional neighbor discovery method, device and electronic device based on asynchronous scanning, which are used to solve the technical problems of delay and high energy consumption of node clusters in the neighbor discovery process in the directional neighbor discovery method based on asynchronous scanning in the related art.

[0006] The present invention provides a directional neighbor discovery method based on asynchronous scanning, comprising the following steps: obtaining node cluster neighbor information, wherein the node cluster neighbor information includes neighbor information of each node in the node cluster; inputting the node cluster neighbor information into an objective function, iteratively calculating the optimal solution of the objective function based on constraints, and obtaining target configuration parameters corresponding to the optimal solution, wherein the objective function is a positive term, the constraints are positive term constraints, the objective function and the constraints constitute a geometric programming problem, the target configuration parameters include a sector selection strategy and a listening time strategy for each node in the node cluster, and the objective function is used to minimize the average neighbor discovery time of the neighbor discovery process. Alternatively, the average energy consumption of the neighbor discovery process is minimized; each node of the node cluster is used as a target node to perform the following steps based on the target configuration parameters, wherein the target configuration parameters include the probability of the target node selecting each sector and the average listening time: determining the target sector based on a first random number and the probability of the target node selecting each sector; determining the target listening time based on a second random number and the average listening time, wherein the first random number is a random number in the range of 0 to 1 that conforms to a uniform distribution law, and the second random number is a random number greater than 0; controlling the target node to select the target sector, enter the listening mode after sending a neighbor discovery request, and maintain the target listening time.

[0007] According to a directional neighbor discovery method based on asynchronous scanning provided by the present invention, the node cluster neighbor information includes neighbor information of each node in the node cluster on each antenna sector.

[0008] According to a directional neighbor discovery method based on asynchronous scanning provided by the present invention, the sector selection strategy includes the probability of a node selecting each antenna sector during the neighbor discovery process, and the listening time strategy includes the listening time of the node after sending a signal.

[0009] According to a directional neighbor discovery method based on asynchronous scanning provided by the present invention, the constraint conditions include:

[0010] ;

[0011] ;

[0012] in, is the set of all antenna sectors of node i; Select antenna sector for node i probability; Select antenna sector for node j probability; is the antenna sector in node i pointing from node i to node j; is the antenna sector in node j pointing from node j to node i; is the listening time of node i after sending the signal; is the listening time of node j after sending the signal; are auxiliary variables used to transform the problem into a geometric programming form; , is the set of all neighbor nodes of node i; is the node i in the antenna sector The set of all neighbor nodes in ; represents the sum of requests from all nodes i.

[0013] According to a directional neighbor discovery method based on asynchronous scanning provided by the present invention, the objective function is used to minimize the average neighbor discovery time of the neighbor discovery process, and the objective function is:

[0014] ;

[0015] in, , is the node cluster; ; , Before the harmonic series Item part and, , Represents the total number of neighbor nodes of node i.

[0016] According to a directional neighbor discovery method based on asynchronous scanning provided by the present invention, the objective function is used to minimize the average energy consumption of the neighbor discovery process, and the objective function is:

[0017] ;

[0018] The constraints also include:

[0019] ;

[0020] in, , is the node cluster; ; , Before the harmonic series Item part and, , Represents the total number of neighbor nodes of node i; are auxiliary variables used to transform the problem into a geometric programming form; is the power of node i when performing signal receiving action; is the power of node i when performing signal sending action; is the power of node i when performing signal listening action.

[0021] The present invention also provides a directional neighbor discovery device based on asynchronous scanning, comprising the following modules: an acquisition module, used to acquire node cluster neighbor information, wherein the node cluster neighbor information includes the neighbor information of each node in the node cluster; a calculation module, used to input the node cluster neighbor information into an objective function, iteratively calculate the optimal solution of the objective function based on constraints, and obtain target configuration parameters corresponding to the optimal solution, wherein the objective function is a positive term, the constraints are positive term constraints, the objective function and the constraints constitute a geometric programming problem, the target configuration parameters include the sector selection strategy and listening time strategy of each node in the node cluster, and the objective function is used to minimize the average neighbor discovery process. present time, or, minimize the average energy consumption of the neighbor discovery process; an execution module, used to take each node of the node cluster as a target node and perform the following steps based on the target configuration parameters, wherein the target configuration parameters include the probability of the target node selecting each sector and the average listening time: determine the target sector based on a first random number and the probability of the target node selecting each sector; determine the target listening time based on a second random number and the average listening time, wherein the first random number is a random number in the range of 0 to 1 that conforms to the uniform distribution law, and the second random number is a random number greater than 0; control the target node to select the target sector, enter the listening mode after sending the neighbor discovery request and maintain the target listening time.

[0022] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the directional neighbor discovery method based on asynchronous scanning as described above is implemented.

[0023] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the method for directional neighbor discovery based on asynchronous scanning as described in any one of the above is implemented.

[0024] The present invention also provides a computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the computer program implements any of the above-mentioned directional neighbor discovery methods based on asynchronous scanning.

[0025] The present invention provides a directional neighbor discovery method, device and electronic device based on asynchronous scanning, which obtain node cluster neighbor information, wherein the node cluster neighbor information includes the neighbor information of each node in the node cluster; the node cluster neighbor information is input into the objective function, and the optimal solution of the objective function is iteratively calculated based on the constraints to obtain the target configuration parameters corresponding to the optimal solution, wherein the objective function is a positive term, the constraints are positive terms, the objective function and the constraints constitute a geometric programming problem, the target configuration parameters include the sector selection strategy and the listening time strategy of each node in the node cluster, and the objective function is used to minimize the average neighbor discovery time of the neighbor discovery process, or minimize the average energy consumption of the neighbor discovery process; the node cluster is controlled to perform neighbor discovery based on the target configuration parameters; the node cluster performs neighbor discovery based on the target configuration parameters to minimize the discovery time or energy consumption in the neighbor discovery process, thereby solving the technical problems of the directional neighbor discovery method based on asynchronous scanning in the related art, which has the delay and high energy consumption of the node cluster in the neighbor discovery process. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced one by one below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0027] Figure 1 It is a flow chart of the directional neighbor discovery method based on asynchronous scanning provided by the present invention.

[0028] Figure 2 This is one of the schematic diagrams of the directional neighbor discovery method based on asynchronous scanning provided by the present invention.

[0029] Figure 3 This is the second schematic diagram of the directional neighbor discovery method based on asynchronous scanning provided by the present invention.

[0030] Figure 4 It is a structural schematic diagram of a directional neighbor discovery device based on asynchronous scanning provided by the present invention.

[0031] Figure 5 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0032] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0033] It should be noted that in the description of the present invention, the terms "include", "comprise" or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "include one..." do not exclude the existence of other identical elements in the process, method, article or device including the elements. The orientation or position relationship indicated by the terms "upper", "lower" and the like is based on the orientation or position relationship shown in the drawings, which is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation of the present invention. Unless otherwise clearly specified and limited, the terms "installed", "connected" and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be an indirect connection through an intermediate medium, or it can be a connection between the two elements. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0034] The terms "first", "second", etc. in the present invention are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances, so that the embodiments of the present invention can be implemented in an order other than those illustrated or described herein, and the objects distinguished by "first", "second", etc. are generally of the same type, and the number of objects is not limited. For example, the first object can be one or more. In addition, "and / or" means at least one of the connected objects, and the character " / " generally indicates that the objects associated with each other are in an "or" relationship.

[0035] The present application relates to the field of communication technology, in particular to a directional antenna communication system in an unmanned aerial vehicle (UAV) cluster, and specifically to a fast neighbor discovery method in an asynchronous directional antenna communication system. In recent years, directional antenna technology, in particular array antennas, multiple-input multiple-output (MIMO) and other technologies have been increasingly widely used in communication systems. These technologies use different angles of space and the diversity of channels to improve the reliability, throughput and energy efficiency of communication, and are particularly suitable for drone clusters, mobile communications, the fifth generation mobile communication technology (5G) and the Internet of Things (IoT) system. Compared with omnidirectional antennas, directional antennas can focus signals in a specific direction, greatly improving the transmission distance and quality of signals and reducing interference. Neighbor discovery is a crucial process in communication networks, which refers to nodes identifying other communicable nodes around them by broadcasting and receiving signals. This process is the basis of many network protocols and applications, especially in drone clusters, wireless sensor networks and IoT systems. The efficiency of neighbor discovery directly affects the overall performance of the network.

[0036] However, the use of directional antennas brings significant difficulties in the neighbor discovery process, mainly because they can only transmit and receive signals in specific directions, which requires nodes to scan neighbors in each direction, increasing discovery time and complexity. At the same time, the signal directions between nodes must be aligned for communication, which is particularly difficult in asynchronous or highly dynamic networks. In addition, the multiple scanning and monitoring processes of directional antennas will significantly increase energy consumption, making neighbor discovery more time-consuming and energy-intensive.

[0037] In scenarios without infrastructure, such as emergency rescue, it is impossible to rely on full network synchronization. In addition, the asynchronous system structure is simpler, the cost is lower, and there is no need for complex synchronization mechanisms. It can better adapt to highly dynamic and decentralized network environments, making it more flexible and adaptable in scenarios such as drone clusters and temporary communication networks. However, in an asynchronous environment, due to time inconsistency, it brings difficulties to the alignment of antennas for communication, further deteriorating the performance of discovering neighbors.

[0038] In asynchronous directional antenna systems, due to the inconsistency of clocks between nodes, the traditional omnidirectional antenna neighbor discovery method is difficult to fully utilize the advantages of directional antennas. In order to adapt to the asynchronous environment, related technologies mostly rely on designing some scanning strategies, trying to improve the success rate of neighbor discovery by increasing the probability of scanning results. However, this method is not efficient in directional antenna systems, especially in asynchronous systems, where nodes cannot predict the communication status of neighbor nodes, resulting in a significant increase in delay and energy consumption in the discovery process.

[0039] The existing asynchronous directional antenna neighbor discovery method has the following shortcomings when facing array antenna technology:

[0040] Latency issue: Due to the lack of synchronization between nodes, directional antennas need to scan in multiple directions step by step, and the scanning is relatively fixed, which cannot specifically adapt to the network topology, resulting in a significant increase in the time for neighbor discovery;

[0041] Energy consumption issue: Compared with traditional omnidirectional antennas, directional antennas have higher directional gain but often have higher energy consumption. The asynchronous system further reduces the probability of successful scanning, resulting in increased energy consumption.

[0042] It can be seen that the directional neighbor discovery method based on asynchronous scanning in the related art has technical problems such as delay and high energy consumption of the node cluster during the neighbor discovery process.

[0043] In order to at least solve some of the above problems, the following Figure 1-Figure 4 The invention describes a method, a device and an electronic device for directional neighbor discovery based on asynchronous scanning.

[0044] The directional neighbor discovery method based on asynchronous scanning provided in this embodiment can be applied to the scenario where the neighbor discovery process is performed on the node cluster based on the directional antenna technology. Here, the neighbor discovery method is performed based on asynchronous scanning. The directional neighbor discovery method based on asynchronous scanning provided in this embodiment can be performed by a node cluster system, and the node cluster can be a drone cluster; the directional neighbor discovery method based on asynchronous scanning provided in this embodiment can be applied to a hardware environment including a drone cluster and a server. Each drone in the drone cluster is connected to the server in communication. The directional neighbor discovery method based on asynchronous scanning in this embodiment can be performed by the server.

[0045] Figure 1 This is one of the flow charts of the directional neighbor discovery method based on asynchronous scanning provided by the present invention, such as Figure 1 As shown, including but not limited to the following steps:

[0046] Step 101 : Obtain node cluster neighbor information, wherein the node cluster neighbor information includes neighbor information of each node in the node cluster.

[0047] Optionally, the node cluster neighbor information includes neighbor information of each node in the node cluster on each antenna sector.

[0048] The node cluster in this embodiment implements the neighbor discovery process based on directional antenna technology. The antenna of each node is divided into multiple antenna sectors to cover the entire airspace. Each antenna sector covers different directions of the node, ensuring that the node can communicate in any direction. Unlike synchronous systems, there is no global time reference between nodes in asynchronous systems. Each node independently decides when to send or receive signals, so a more flexible communication mechanism is required.

[0049] In an asynchronous system, the neighbor discovery process is completed through independent operations between nodes. Since there is no synchronized time reference, nodes cannot rely on time slots to coordinate each other's sending and receiving operations. Therefore, the neighbor discovery process adopts the following basic communication structure:

[0050] Each node completes the communication attempt through a neighbor discovery request sending operation (i.e., signal sending action) followed by a random listening period. When initiating a neighbor discovery request, the node randomly selects an antenna sector to send the signal. After the transmission is completed, the node will randomly listen for a period of time in the current sector to receive requests from other nodes.

[0051] It should be noted that there are two states of a node in the neighbor discovery process, the signal sending state and the signal receiving state. The listening state refers to the state in which the node is in the signal receiving state but has not received any signal.

[0052] During this process, the two nodes can successfully complete neighbor discovery only if the following conditions are met: the two nodes must select sectors that point to each other for operation; one node is in the sending state and the other node is in the receiving state in the same sector; there is no interference from other nodes during the neighbor discovery process to ensure that the signal can be successfully transmitted.

[0053] When the above conditions are met, the two nodes can complete neighbor discovery in this time slot. Figure 2 is one of the schematic diagrams of the directional neighbor discovery method based on asynchronous scanning provided by the present invention, such as Figure 2 As shown, Figure 2An example of node i discovering node j is shown. Node i and node j are paired through node i's antenna sector 3 and node j's antenna sector 7, and node i and node k are paired through node i's antenna sector 3 and node k's antenna sector 7. When node i and node j are paired successfully for the first time, node i is in a receiving state and node j is in a sending state, but at the same time, the antenna sector selected by node k is also antenna sector 7. Since node i can only receive signals from one node, node j and node k send signals to node i at the same time, causing conflict interference. At this time, node i cannot discover node j. When node i and node j are paired for the second time, node i is in a receiving state and node j is in a sending state, and the antenna sector selected by node k is antenna sector 6. There is no conflict, and node i discovers node j.

[0054] In this embodiment, node cluster neighbor information is obtained, wherein the node cluster neighbor information includes neighbor information of each node in the node cluster, that is, the node cluster neighbor information includes topological information between each node and all neighbor nodes, for example, Figure 2 In the example, node i can discover node j and node k, then the neighbor information of node i includes node j and node k.

[0055] The node cluster neighbor information includes information about neighbor nodes corresponding to each node in the node cluster in each antenna sector. For example, Figure 2 In the example, antenna sector 3 of node i can discover antenna sector 7 of node j and antenna sector 7 of node k. In addition, other antenna sectors of node i can also include other discoverable nodes.

[0056] Step 102, input the node cluster neighbor information into the objective function, iteratively calculate the optimal solution of the objective function based on the constraints, and obtain the target configuration parameters corresponding to the optimal solution, wherein the objective function is a positive term, the constraints are positive terms, the objective function and the constraints constitute a geometric programming problem, the target configuration parameters include the sector selection strategy and listening time strategy of each node in the node cluster, and the objective function is used to minimize the average neighbor discovery time of the neighbor discovery process, or minimize the average energy consumption of the neighbor discovery process.

[0057] Optionally, the sector selection strategy includes the probability of the node selecting each antenna sector when performing a neighbor discovery process, and the listening time strategy includes the listening time of the node after sending a signal.

[0058] Step 103: Take each node in the node cluster as a target node and perform the following steps based on target configuration parameters, wherein the target configuration parameters include the probability of the target node selecting each sector and the average listening time:

[0059] Step 1031, determining a target sector based on a first random number and a probability of the target node selecting each sector;

[0060] Step 1032, determining the target listening time based on the second random number and the average listening time, wherein the first random number is a random number in the range of 0 to 1 that conforms to a uniform distribution rule, and the second random number is a random number greater than 0;

[0061] Step 1033, control the target node to select a target sector, enter a listening mode after sending a neighbor discovery request, and maintain a target listening time.

[0062] It should be noted that a positive polynomial is a polynomial whose coefficients are all positive. That is, if each term of a polynomial is a non-negative real product of variable powers and all coefficients are positive, then the polynomial is a positive polynomial. Geometric programming is an optimization problem in which the objective function and constraints are functions of positive polynomials.

[0063] In this embodiment, a pre-constructed geometric programming problem is involved. The geometric programming problem includes an objective function and constraints. The objective function and constraints together define an optimization problem. The optimization problem in this embodiment is to minimize the average neighbor discovery time of the neighbor discovery process, or to minimize the average energy consumption of the neighbor discovery process; here, the average neighbor discovery time refers to the average time for each node in the node cluster to discover its neighbor nodes, and the average energy consumption refers to the average energy consumption for each node in the node cluster to discover its neighbor nodes.

[0064] The optimal solution of the objective function is iteratively calculated based on the constraints. The optimal solution corresponds to the target configuration parameters. Controlling the node cluster to perform neighbor discovery based on the target configuration parameters can minimize the average neighbor discovery time and the average energy consumption of the node cluster performing the neighbor discovery process.

[0065] In this embodiment, the objective function determines the optimization direction and the optimal value of the final solution, while the constraints determine the feasible region of the solution. The optimal solution must simultaneously satisfy the optimality of the objective function and the feasibility of the constraints. Here, in the solution process, the geometric programming problem can be rewritten as a convex problem, and then the convex problem is solved using the convex optimization method. Any local optimal solution obtained is the global optimal solution.

[0066] Through the embodiments provided by the present application, node cluster neighbor information is obtained, wherein the node cluster neighbor information includes neighbor information of each node in the node cluster; the node cluster neighbor information is input into the objective function, and the optimal solution of the objective function is iteratively calculated based on the constraints to obtain the target configuration parameters corresponding to the optimal solution, wherein the objective function is a positive term, the constraints are positive term constraints, the objective function and the constraints constitute a geometric programming problem, the target configuration parameters include the sector selection strategy and the listening time strategy of each node in the node cluster, and the objective function is used to minimize the average neighbor discovery time of the neighbor discovery process, or minimize the average energy consumption of the neighbor discovery process; each node of the node cluster is used as the target node based on the target configuration. The target configuration parameters are set to perform the following steps, wherein the target configuration parameters include the probability of the target node selecting each sector and the average listening time: determining the target sector based on a first random number and the probability of the target node selecting each sector; determining the target listening time based on a second random number and the average listening time, wherein the first random number is a random number in a range of 0 to 1 that conforms to a uniform distribution law, and the second random number is a random number greater than 0; controlling the target node to select the target sector, enter the listening mode after sending a neighbor discovery request, and maintain the target listening time; solving the technical problems of the delay and high energy consumption of the node cluster in the neighbor discovery process in the directional neighbor discovery method based on asynchronous scanning in the related art, thereby improving the efficiency of neighbor discovery.

[0067] As an optional solution, the constraints include:

[0068] ;

[0069] ;

[0070] in, is the set of all antenna sectors of node i; Select antenna sector for node i probability; Select antenna sector for node j probability; is the antenna sector in node i pointing from node i to node j; is the antenna sector in node j pointing from node j to node i; is the listening time of node i after sending the signal; is the listening time of node j after sending the signal; are auxiliary variables used to transform the problem into a geometric programming form; , is the set of all neighbor nodes of node i; is the node i in the antenna sector The set of all neighbor nodes in ; represents the sum of requests from all nodes i.

[0071] As an optional solution, the objective function is used to minimize the average neighbor discovery time of the neighbor discovery process. The objective function is:

[0072] ;

[0073] in, , For node clusters; ; , Before the harmonic series Item part and, , Represents the total number of neighbor nodes of node i.

[0074] As an optional solution, the objective function is used to minimize the average energy consumption of the neighbor discovery process. The objective function is:

[0075] ;

[0076] The constraints also include:

[0077] ;

[0078] in, , For node clusters; ; , Before the harmonic series Item part and, , Represents the total number of neighbor nodes of node i; are auxiliary variables used to transform the problem into a geometric programming form; is the power of node i when performing signal receiving action; is the power of node i when performing signal sending action; is the power of node i when performing signal listening action.

[0079] It should be noted that there are two states of nodes in the neighbor discovery process, signal sending state and signal receiving state. When the node is in the signal receiving state but has not received a signal, the power of the node at this time is the power when the node performs a signal listening action; when the node is in the signal receiving state and receives a signal, the power of the node at this time is the power when the node performs a signal receiving action; when the node is in the signal sending state, the power of the node at this time is the power when the node performs a signal sending action.

[0080] In the basic asynchronous neighbor discovery method, the node's sector selection and sending / receiving timing are random, resulting in unpredictable time and energy consumption for neighbor discovery. Especially when the number of nodes increases or the topology is complex, the discovery delay and energy consumption will increase significantly.

[0081] To solve this problem, this application proposes a neighbor discovery solution based on convex optimization. By constructing an optimization model, the optimization goal is to generate target configuration parameters. These parameters include the probability of a node selecting each antenna sector during the neighbor discovery process. and the listening time of the node after sending the signal .

[0082] During the neighbor discovery process, nodes perform neighbor discovery according to the target configuration parameters: each node selects the optimal sector probability according to the optimized sector selection probability when initiating a neighbor discovery request. Select an antenna sector to send the signal; after the transmission is completed, the node listens according to the optimized listening time Listening in the current sector, waiting for requests from potential neighbor nodes.

[0083] In this embodiment, the process of iteratively calculating the optimal solution of the objective function based on the constraint conditions may include the following steps:

[0084] Step 1: Determine the optimization objective, that is, select one of the two optimization objectives: minimizing the average neighbor discovery time / minimizing the average energy consumption.

[0085] Step 2: Convert the selected problem into a linear form, perform logarithmic transformation on the power terms and product forms in the objective function, and convert the original variables , , Transform into logarithmic form, thereby converting nonlinear functions into linear form, and then converting geometric programming problems into convex problems.

[0086] Step 3: Initialize the transmission and reception probability and sector selection probability, , , and the convergence accuracy Used to control the convergence speed and accuracy. Auxiliary variables can be set to , , is the total number of nodes.

[0087] Step 4: Use the Interior Point Method (IPM) algorithm to iteratively update the optimization variables according to the objective function and constraints, and gradually approach the optimal solution. It is necessary to ensure that the constraints are met during the iteration process. In each iteration, solve the Karush-Kuhn-Tucker (KKT) condition to ensure that the solution meets the constraints of the optimization problem.

[0088] Step 5: When the iteration meets the preset convergence accuracy Stop iteration and output the solution result , , that is, the target configuration parameters corresponding to the optimal solution.

[0089] In this embodiment, after obtaining the target configuration parameters, each node in the node cluster needs to be used as a target node to perform the following steps based on the target configuration parameters, wherein the target configuration parameters include the probability of the target node selecting each sector and the average listening time:

[0090] determining a target sector based on the first random number and a probability of the target node selecting each sector;

[0091] Determining the target listening time based on a second random number and the average listening time, wherein the first random number is a random number in a range from 0 to 1 that conforms to a uniform distribution law, and the second random number is a random number greater than 0;

[0092] Control the target node to select the target sector, enter the listening mode after sending the neighbor discovery request, and maintain the target listening time.

[0093] It should be noted that for the node , the target configuration parameters include and ;Right now, For Node Select Sector The probability of, here, Include Node All sectors of For Node The average length of random listening time after a request is sent, i.e., the average listening time.

[0094] Figure 3 This is a schematic diagram of the second directional neighbor discovery method based on asynchronous scanning provided by the present invention. Figure 3 The above steps are explained.

[0095] The target sector is determined based on the first random number and the probability of the target node selecting each sector; specifically, before each neighbor discovery message is sent, the target node randomly generates a uniformly distributed first random number, for example, Randomly generate random numbers , whose range is , used to determine the node in the current time slot The working sector can be determined by the following inequality:

[0096] ;

[0097] in, Representation Node Sector The selection probability of ; when n satisfies the above inequality, the target sector is determined to be sector n.

[0098] The target listening time is determined based on the second random number and the average listening time, wherein the second random number is a random number greater than 0; specifically, the node Generate another uniformly distributed random number , the second random number The parameters are satisfied Negative exponential distribution, the second random number Used to determine the target listening time; the target listening time is ,here, The length of a neighbor discovery request.

[0099] The target node is controlled to select the target sector, enter the listening mode after sending the neighbor discovery request and maintain the target listening time; in the asynchronous system, the node's neighbor discovery process consists of independent sending and listening operations: after the node sends the neighbor discovery request in the selected sector, it will listen for a certain period of time; if a response message is received from the neighbor within the listening time, the neighbor will be recorded in the neighbor table; if the preset number of neighbors is not reached, the node will generate a random number again and repeat the process of selecting the sector and listening time until all neighbors are found.

[0100] The solution of this application includes the following technical effects:

[0101] 1. Significantly shortened neighbor discovery time: Through convex optimization of the sector selection probability and listening time generated, this scheme significantly improves the matching probability between nodes and reduces the time required for neighbor discovery. Compared with a completely random operation mode, nodes can discover neighboring nodes in a shorter time, greatly improving the efficiency of neighbor discovery, which is particularly suitable for the dynamic network environment in asynchronous systems.

[0102] 2. Significantly reduced energy consumption: This scheme optimizes the average listening time of the node and avoids unnecessary long-term listening operations, thereby effectively reducing energy consumption. The operation of the node is optimized at each step to ensure energy saving while reducing invalid operations, which is especially important for wireless communication networks with limited resources (such as drone networks).

[0103] 3. Strong adaptability and flexibility in dealing with asynchronous environments: There is no global time reference in asynchronous systems, and the operation of nodes is highly random. This solution adapts to this uncertainty by optimizing the operation probability of each node, enabling nodes to flexibly respond to dynamic changes in the network and maintain efficient neighbor discovery capabilities in an environment without time synchronization.

[0104] 4. Reduce communication interference: The optimization model takes into account the communication interference between nodes, and reduces signal conflicts and interference problems by reasonably allocating the operation timing and direction of the nodes. This mechanism improves the success rate of neighbor discovery, especially in multi-node, high-density asynchronous networks, and can significantly improve communication quality.

[0105] 5. Intelligent optimization based on prior information: This solution uses prior topological information (relative positions of nodes and possible neighbor distributions) and makes intelligent decisions through convex optimization technology, so that nodes can select the optimal sector and listening time based on this information in actual operations, improving the accuracy and effectiveness of operations and avoiding the blindness in traditional neighbor discovery.

[0106] Through this embodiment, by constructing and solving a geometric programming problem, the sector selection probability and the average listening time of the node can be flexibly adjusted. Through these adjustable parameters, the system can be adjusted according to the dynamic needs in the asynchronous network, significantly improving the efficiency of neighbor discovery, reducing discovery delays, and optimizing energy consumption, so that the solution can adapt to different network topologies and environments; before the neighbor discovery process begins, the geometric programming problem is converted into a convex problem, and key configuration parameters are generated based on convex optimization technology, including the selection probability of each sector and the average listening time of the node. These parameters enable the node to efficiently complete neighbor discovery in an asynchronous environment, ensuring that the discovery process reaches the optimal state in terms of time and energy consumption, which is particularly suitable for communication scenarios without a global time reference in asynchronous systems.

[0107] Figure 4 is a schematic diagram of the structure of a directional neighbor discovery device based on asynchronous scanning provided by the present invention, such as Figure 4 As shown, including but not limited to the following modules:

[0108] An acquisition module 401 is used to acquire node cluster neighbor information, wherein the node cluster neighbor information includes neighbor information of each node in the node cluster;

[0109] The calculation module 402 is used to input the node cluster neighbor information into the objective function, iteratively calculate the optimal solution of the objective function based on the constraint condition, and obtain the target configuration parameters corresponding to the optimal solution, wherein the objective function is a positive term, the constraint condition is a positive term constraint, the objective function and the constraint condition constitute a geometric programming problem, the target configuration parameters include the sector selection strategy and the listening time strategy of each node in the node cluster, and the objective function is used to minimize the average neighbor discovery time of the neighbor discovery process, or minimize the average energy consumption of the neighbor discovery process;

[0110] The execution module 403 is used to use each node of the node cluster as a target node to perform the following steps based on the target configuration parameters, wherein the target configuration parameters include the probability of the target node selecting each sector and the average listening time:

[0111] determining a target sector based on the first random number and a probability of the target node selecting each sector;

[0112] Determining the target listening time based on a second random number and the average listening time, wherein the first random number is a random number in a range from 0 to 1 that conforms to a uniform distribution law, and the second random number is a random number greater than 0;

[0113] Control the target node to select the target sector, enter the listening mode after sending the neighbor discovery request, and maintain the target listening time.

[0114] Through the embodiments of the present application, node cluster neighbor information is obtained, wherein the node cluster neighbor information includes neighbor information of each node in the node cluster; the node cluster neighbor information is input into the objective function, and the optimal solution of the objective function is iteratively calculated based on the constraints to obtain the target configuration parameters corresponding to the optimal solution, wherein the objective function is a positive term, the constraints are positive term constraints, the objective function and the constraints constitute a geometric programming problem, the target configuration parameters include the sector selection strategy and the listening time strategy of each node in the node cluster, and the objective function is used to minimize the average neighbor discovery time of the neighbor discovery process, or minimize the average energy consumption of the neighbor discovery process; each node of the node cluster is used as a target node based on the target configuration The parameters perform the following steps, wherein the target configuration parameters include the probability of the target node selecting each sector and the average listening time: determining the target sector based on the first random number and the probability of the target node selecting each sector; determining the target listening time based on the second random number and the average listening time, wherein the first random number is a random number in the range of 0 to 1 that conforms to the uniform distribution law, and the second random number is a random number greater than 0; controlling the target node to select the target sector, enter the listening mode after sending a neighbor discovery request and maintain the target listening time; solving the technical problems of the directional neighbor discovery method based on asynchronous scanning in the related technology, the delay of the node cluster in the neighbor discovery process and the high energy consumption, and improving the efficiency of neighbor discovery.

[0115] It should be noted that the directional neighbor discovery device based on asynchronous scanning provided by the present invention can execute the directional neighbor discovery method based on asynchronous scanning of any of the above embodiments during specific operation, which will not be elaborated in this embodiment.

[0116] Figure 5 is a schematic diagram of the structure of the electronic device provided by the present invention, such as Figure 5 As shown, the electronic device may include: a processor 510, a communication interface 520, a memory 530 and a communication bus 540, wherein the processor 510, the communication interface 520 and the memory 530 communicate with each other through the communication bus 540. The processor 510 may call the logic instructions in the memory 530 to execute a directional neighbor discovery method based on asynchronous scanning, the method comprising: obtaining node cluster neighbor information, wherein the node cluster neighbor information includes neighbor information of each node in the node cluster; inputting the node cluster neighbor information into the objective function, iteratively calculating the optimal solution of the objective function based on the constraint conditions, and obtaining the target configuration parameters corresponding to the optimal solution, wherein the objective function is a positive term, the constraint conditions are positive term constraints, the objective function and the constraint conditions constitute a geometric programming problem, the target configuration parameters include the sector selection strategy and the listening time strategy of each node in the node cluster, and the objective function is used to minimize the neighbor discovery process. Average neighbor discovery time, or, minimize the average energy consumption of the neighbor discovery process; take each node of the node cluster as a target node and perform the following steps based on the target configuration parameters, wherein the target configuration parameters include the probability of the target node selecting each sector and the average listening time: determine the target sector based on a first random number and the probability of the target node selecting each sector; determine the target listening time based on a second random number and the average listening time, wherein the first random number is a random number in the range of 0 to 1 that conforms to the uniform distribution law, and the second random number is a random number greater than 0; control the target node to select the target sector, enter the listening mode after sending a neighbor discovery request, and maintain the target listening time.

[0117] In addition, the logic instructions in the above-mentioned memory 530 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for 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 of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0118] On the other hand, the present invention also provides a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium, and the computer program includes program instructions. When the program instructions are executed by a computer, the computer can execute the directional neighbor discovery method based on asynchronous scanning provided by the above-mentioned embodiments, and the method includes: obtaining node cluster neighbor information, wherein the node cluster neighbor information includes the neighbor information of each node in the node cluster; inputting the node cluster neighbor information into an objective function, iteratively calculating the optimal solution of the objective function based on constraints, and obtaining target configuration parameters corresponding to the optimal solution, wherein the objective function is a positive term, and the constraints are positive term constraints. The objective function and the constraints constitute a geometric programming problem, and the target configuration parameters include the node cluster. The sector selection strategy and listening time strategy of each node, the objective function is used to minimize the average neighbor discovery time of the neighbor discovery process, or minimize the average energy consumption of the neighbor discovery process; each node of the node cluster is used as a target node to perform the following steps based on the target configuration parameters, wherein the target configuration parameters include the probability of the target node selecting each sector and the average listening time: determine the target sector based on a first random number and the probability of the target node selecting each sector; determine the target listening time based on a second random number and the average listening time, wherein the first random number is a random number in the range of 0 to 1 that conforms to the uniform distribution law, and the second random number is a random number greater than 0; control the target node to select the target sector, enter the listening mode after sending a neighbor discovery request, and maintain the target listening time.

[0119] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which is implemented when the processor executes the directional neighbor discovery method based on asynchronous scanning provided in the above-mentioned embodiments, the method comprising: obtaining node cluster neighbor information, wherein the node cluster neighbor information includes neighbor information of each node in the node cluster; inputting the node cluster neighbor information into an objective function, iteratively calculating the optimal solution of the objective function based on constraints, and obtaining target configuration parameters corresponding to the optimal solution, wherein the objective function is a positive term, the constraints are positive term constraints, the objective function and the constraints constitute a geometric programming problem, and the target configuration parameters include the sector selection strategy and listening time of each node in the node cluster. Strategy, the objective function is used to minimize the average neighbor discovery time of the neighbor discovery process, or minimize the average energy consumption of the neighbor discovery process; each node of the node cluster is used as a target node to perform the following steps based on the target configuration parameters, wherein the target configuration parameters include the probability of the target node selecting each sector and the average listening time: determine the target sector based on a first random number and the probability of the target node selecting each sector; determine the target listening time based on a second random number and the average listening time, wherein the first random number is a random number in the range of 0 to 1 that conforms to the uniform distribution law, and the second random number is a random number greater than 0; control the target node to select the target sector, enter the listening mode after sending a neighbor discovery request, and maintain the target listening time.

[0120] The device embodiments described above are merely illustrative, wherein 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, i.e., they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Those of ordinary skill in the art may understand and implement it without creative effort.

[0121] Through the description of the above implementation modes, those skilled in the art can clearly understand that each implementation mode can be implemented by means of software plus a necessary general hardware platform, or of course by hardware. Based on such an understanding, the above technical solution can essentially or in other words be embodied in the form of a software product that contributes to the prior art. The computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods of each embodiment or some parts of the embodiment.

[0122] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A directional neighbor discovery method based on asynchronous scanning, characterized in that: include: Obtaining node cluster neighbor information, wherein the node cluster neighbor information includes neighbor information of each node in the node cluster; Inputting the node cluster neighbor information into an objective function, iteratively calculating the optimal solution of the objective function based on constraints, and obtaining target configuration parameters corresponding to the optimal solution, wherein the objective function is a positive term, the constraints are positive term constraints, the objective function and the constraints constitute a geometric programming problem, the target configuration parameters include a sector selection strategy and a listening time strategy for each node in the node cluster, and the objective function is used to minimize the average neighbor discovery time of a neighbor discovery process, or minimize the average energy consumption of a neighbor discovery process; Each node of the node cluster is used as a target node and the following steps are performed based on the target configuration parameters, wherein the target configuration parameters include the probability of the target node selecting each sector and the average listening time: determining a target sector based on a first random number and a probability of the target node selecting each sector; Determining a target listening time based on a second random number and the average listening time, wherein the first random number is a random number in a range from 0 to 1 that conforms to a uniform distribution rule, and the second random number is a random number greater than 0; The target node is controlled to select the target sector, enter a listening mode after sending a neighbor discovery request, and maintain the target listening time.

2. The method for directional neighbor discovery based on asynchronous scanning according to claim 1, characterized in that: The node cluster neighbor information includes neighbor information of each node in the node cluster on each antenna sector.

3. The method for directional neighbor discovery based on asynchronous scanning according to claim 1, characterized in that: The sector selection strategy includes the probability of a node selecting each antenna sector when performing a neighbor discovery process, and the listening time strategy includes the listening time of a node after sending a signal.

4. The method for directional neighbor discovery based on asynchronous scanning according to any one of claims 1 to 3, characterized in that: The constraints include: ； ； in, is the set of all antenna sectors of node i; Select antenna sector for node i probability; Select antenna sector for node j probability; is the antenna sector in node i pointing from node i to node j; is the antenna sector in node j pointing from node j to node i; is the listening time of node i after sending the signal; is the listening time of node j after sending the signal; are auxiliary variables used to transform the problem into a geometric programming form; , is the set of all neighbor nodes of node i; is the node i in the antenna sector The set of all neighbor nodes in ; represents the sum of requests from all nodes i.

5. The method for directional neighbor discovery based on asynchronous scanning according to claim 4, characterized in that: The objective function is used to minimize the average neighbor discovery time of the neighbor discovery process, and the objective function is: ； in, , is the node cluster; ; Before the harmonic series Item part and, Represents the total number of neighbor nodes of node i.

6. The method for directional neighbor discovery based on asynchronous scanning according to claim 4, characterized in that: The objective function is used to minimize the average energy consumption of the neighbor discovery process, and the objective function is: ； The constraints also include: ； in, is the average energy consumption of node i during neighbor discovery, , is the node cluster; ; Before the harmonic series Item part and, Represents the total number of neighbor nodes of node i; the constraint condition is used to Apply appropriate constraints to ensure that the problem satisfies the form of geometric programming; is the power of node i when performing signal receiving action; is the power of node i when performing signal sending action; is the power of node i when performing signal listening action.

7. A directional neighbor discovery device based on asynchronous scanning, characterized in that: include: An acquisition module, configured to acquire node cluster neighbor information, wherein the node cluster neighbor information includes neighbor information of each node in the node cluster; A calculation module, used for inputting the node cluster neighbor information into an objective function, iteratively calculating the optimal solution of the objective function based on constraints, and obtaining target configuration parameters corresponding to the optimal solution, wherein the objective function is a positive term, the constraints are positive term constraints, the objective function and the constraints constitute a geometric programming problem, the target configuration parameters include a sector selection strategy and a listening time strategy for each node in the node cluster, and the objective function is used to minimize the average neighbor discovery time of the neighbor discovery process, or minimize the average energy consumption of the neighbor discovery process; An execution module is used to take each node of the node cluster as a target node and perform the following steps based on the target configuration parameters, wherein the target configuration parameters include the probability of the target node selecting each sector and the average listening time: determining a target sector based on a first random number and a probability of the target node selecting each sector; Determining a target listening time based on a second random number and the average listening time, wherein the first random number is a random number in a range from 0 to 1 that conforms to a uniform distribution rule, and the second random number is a random number greater than 0; The target node is controlled to select the target sector, enter a listening mode after sending a neighbor discovery request, and maintain the target listening time.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the directional neighbor discovery method based on asynchronous scanning as described in any one of claims 1 to 6 is implemented.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the directional neighbor discovery method based on asynchronous scanning as claimed in any one of claims 1 to 6 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the directional neighbor discovery method based on asynchronous scanning as claimed in any one of claims 1 to 6 is implemented.

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