Communication scheduling method and device for cooperative encircling of underwater clusters

Abstract

The invention provides a communication scheduling method and device for cooperative encircling of an underwater cluster, the underwater cluster comprises a master node and a slave node, and the method comprises the following steps: the master node carries out cooperative encircling on the basis of a feedback data packet sent by the slave node in a scheduling stage; determining the information value of the current communication data and the feedback data packet transmission success rate of each slave node in the current round of scheduling stage, and further determining the time slot redundancy of the next round of scheduling communication; according to a method of maximizing the average information value of the cluster, determining a node transmission sequence in scheduling communication; the main node adaptively adjusts a scheduling maintenance period according to the closeness and the maximum communication distance between the underwater collaborative surrounding clusters so as to generate a scheduling instruction packet and broadcast the scheduling instruction packet; therefore, the scheduling parameters are dynamically adjusted through the feedback information, so that the support of the communication protocol to the underwater cluster cooperative hunting communication is improved, and the efficiency and success rate of the underwater cluster cooperative hunting task are improved.

Description

Technical Field

[0001] The present application relates to the technical field of cluster control, and particularly relates to a communication scheduling method for underwater cluster cooperative hunting and a communication scheduling device for underwater cluster cooperative hunting. Background Art

[0002] In the related art, Underwater Acoustic Sensor Networks (UASNs) play a key role in ocean monitoring and cooperative tasks, and have important applications especially in fields such as autonomous underwater vehicle (AUV) cluster cooperative hunting, target tracking, and formation control. Traditional underwater communication protocols (such as TDMA, Aloha, Handshake) are mostly designed based on general tasks and have not been optimized for the underwater unmanned cluster cooperative hunting task, lacking adaptability to the dynamic characteristics of underwater acoustic channels (such as high propagation delay, path loss, and low packet delivery rate). For example, existing protocols often adopt fixed time slot division or static scheduling periods, resulting in a significant decrease in the timeliness of information between the command node (master node) and slave nodes in the target hunting task, thereby causing formation cooperation deviation and reducing the hunting success rate. In addition, due to the influence of underwater acoustic channels and energy constraints, traditional Medium Access Control Protocols (MAC) are difficult to balance the Packet Delivery Ratio (PDR) and energy consumption. Especially in dynamic hunting scenarios, frequent scheduling instructions easily lead to premature exhaustion of the command node's energy. Therefore, how to improve the effectiveness and reliability of the cluster communication protocol in this scenario has become a key technical challenge for improving the efficiency of underwater cluster cooperative hunting. Summary of the Invention

[0003] The present application aims to at least partly solve one of the technical problems in the above technologies. For this purpose, an object of the present application is to propose a communication scheduling method for underwater cluster cooperative hunting, which dynamically adjusts scheduling parameters through feedback information to improve the support of the communication protocol for underwater cluster cooperative hunting communication, thereby improving the efficiency and success rate of underwater cluster cooperative hunting tasks.

[0004] A second object of the present application is to propose a communication scheduling device for underwater cluster cooperative hunting.

[0005] To achieve the above object, the present application proposes a communication scheduling method for underwater cluster cooperative hunting. The underwater cluster includes a master node and multiple slave nodes. The communication scheduling method includes the following steps: obtaining an initial scheduling instruction packet and sending it to each slave node, so that each slave node generates a feedback data packet according to the initial scheduling instruction packet. The scheduling instruction packet includes the channel access time and the scheduling maintenance period of each slave node; receiving the feedback data packets sent by each slave node, where the feedback data packet includes the position information and motion state of the slave node itself; calculating the corresponding information value according to the feedback data packet and its reception time to obtain the corresponding quantitative time slot redundancy; using a genetic algorithm to generate the scheduling transmission order of the feedback data packets of each slave node, and obtaining the channel access time of each slave node in the next round according to the quantitative time slot redundancy; calculating the cluster compactness and the maximum communication distance according to the feedback data packet, and obtaining the scheduling maintenance period in the next round according to the cluster compactness and the maximum communication distance; generating a scheduling instruction packet in the next round according to the channel access time of each slave node in the next round and the scheduling maintenance period in the next round for communication scheduling; thus, dynamically adjusting the scheduling parameters through feedback information to improve the support of the communication protocol for underwater cluster cooperative hunting communication, thereby improving the efficiency and success rate of the underwater cluster cooperative hunting task.

[0006] In addition, the communication scheduling method for underwater cluster cooperative hunting proposed by the present application may also have the following additional technical features: Optionally, the scheduling instruction packet further includes formation command information, and the formation command information includes the expected motion positions corresponding to each slave node to dynamically adjust the network topology structure.

[0007] Optionally, each slave node generates a feedback data packet according to the initial scheduling instruction packet, including: each slave node decodes the received initial scheduling instruction packet to obtain the corresponding channel access time and expected motion position; each slave node moves according to the expected motion position and sends its own feedback data packet to the master node at the corresponding channel access time.

[0008] Optionally, calculating the corresponding information value according to the feedback data packet and its reception time to obtain the corresponding quantitative time slot redundancy includes: starting timing before sending the scheduling instruction packet until receiving the feedback data packets of each slave node to stop, so as to obtain the propagation delay corresponding to each slave node; obtaining the information value corresponding to each slave node according to the propagation delay, and obtaining the corresponding quantitative time slot redundancy according to the information value.

[0009] Optionally, the information value corresponding to each slave node is obtained according to the following formula:

[0010] Among them, represents the corresponding information value, represents the initial value of the information value, represents the end-to-end delay, that is, the propagation delay, represents the maximum effective time of the information, and represents the correction parameter.

[0011] Optionally, the quantitative slot redundancy corresponding to each slave node is obtained according to the following formula:

[0012] Among them, represents the quantitative slot redundancy corresponding to the kth slave node, represents the maximum slot redundancy, represents the minimum slot redundancy, represents the information value corresponding to the kth slave node.

[0013] Optionally, a genetic algorithm is used to generate the scheduling transmission order of the feedback data packets of each slave node, including: initializing the sequence set composed of each slave node; constructing a fitness function to evaluate the transmission sequence overhead of each individual in the sequence set, so as to select a fixed number of elite sequence individuals into the next generation; performing crossover and mutation on the elite sequence individuals until the next generation sequence set is filled; calculating the average fitness of the next generation sequence set to obtain the overall mean square error according to the average fitness; calculating the dynamic mutation probability according to the overall mean square error; using the dynamic mutation probability to mutate all sequence individuals in the next generation sequence set, and so on, until the stop condition is met and the scheduling transmission order of the feedback data packets of each slave node is output.

[0014] Optionally, the cluster compactness and the maximum communication distance are calculated according to the following formula:

[0015]

[0016] Among them, represents the cluster compactness, represents the maximum communication distance, , represent the spatial coordinates of the cluster members, , represent the spatial coordinates of the surrounded target, the set of cluster member numbers is [0, n], and the master node number is always fixed at 0.

[0017] Optionally, the scheduling maintenance period of the next round is obtained according to the following formula:

[0018]

[0019] Among them, represents the scheduling maintenance period of the next round, represents the normalization factor of the cluster compactness and the maximum communication distance, which is obtained according to the initial deployment range X×Y of the cluster.

[0020] To achieve the above object, the present application proposes a communication scheduling device for underwater cluster cooperative hunting. The underwater cluster includes a master node and a plurality of slave nodes. The communication scheduling device includes: a sending module, configured to obtain an initial scheduling instruction packet and send it to each slave node, so that each slave node generates a feedback data packet according to the initial scheduling instruction packet. Among them, the scheduling instruction packet includes the channel access time and the scheduling maintenance period of each slave node; a receiving module, configured to receive the feedback data packets sent by each slave node. Among them, the feedback data packet includes the position information and motion state of the slave node itself; a first calculation module, configured to calculate the corresponding information value according to the feedback data packet and its reception time to obtain the corresponding quantitative time slot redundancy; a processing module, configured to use a genetic algorithm to generate the scheduling transmission order of the feedback data packets of each slave node, and obtain the channel access time of each slave node in the next round according to the quantitative time slot redundancy; a second calculation module, configured to calculate the cluster compactness and the maximum communication distance according to the feedback data packet, and obtain the scheduling maintenance period of the next round according to the cluster compactness and the maximum communication distance; a communication scheduling module, configured to generate a scheduling instruction packet for the next round according to the channel access time of each slave node in the next round and the scheduling maintenance period of the next round for communication scheduling; thereby, dynamically adjusting the scheduling parameters through the feedback information to improve the support of the communication protocol for underwater cluster cooperative hunting communication, so as to improve the efficiency and success rate of the underwater cluster cooperative hunting task. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 is a schematic flowchart of a communication scheduling method for underwater cluster cooperative hunting according to an embodiment of the present application; Figure 2 is a schematic scenario diagram of a communication scheduling method for underwater cluster cooperative hunting according to an embodiment of the present application; Figure 3 is a schematic diagram of the scheduling periodic workflow of a communication scheduling method for underwater cluster cooperative hunting according to an embodiment of the present application; Figure 4 is a schematic block diagram of a communication scheduling device for underwater cluster cooperative hunting according to an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0022] Embodiments of the present application will be described in detail below. Examples of the embodiments are shown in the accompanying drawings, where like or similar reference numerals denote like or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the accompanying drawings are exemplary and are intended to explain the present application, and should not be construed as a limitation of the present application.

[0023] To better understand the above technical solution, exemplary embodiments of the present application will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present application are shown in the drawings, it should be understood that the present application can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present application and to fully convey the scope of the present application to those skilled in the art.

[0024] To better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings of the specification and specific implementation manners.

[0025] As Figure 2 shown, the cluster nodes of the system architecture of the present application include a command node (i.e., the master node) and a number of data nodes (i.e., the slave nodes). Among them, the master node and the slave nodes have the same functions, are initially randomly distributed underwater for searching for the target to be surrounded, and the node that first discovers the target to be surrounded will become the master node; all nodes can obtain their own position information and motion states, and at the same time, time synchronization is not required between the cluster nodes.

[0026] During the search process, each cluster node i ( , the set of network nodes) has the same status, but the first cluster node that discovers the target (numbered 0) will become the master node of the surrounding task, and the remaining nodes will become the slave nodes; the master node will continuously perform target tracking, cluster network communication scheduling, and command the slave nodes to form a surrounding formation until the collaborative surrounding is finally completed.

[0027] Assume that the detection function of the AUV can perform reconnaissance and target recognition within a range centered on the individual. When the distance between the AUV and the target is less than , it can perform a surrounding action on the target. When the number of nodes that can perform the surrounding action reaches the surrounding threshold , it is determined that the surrounding task is successful.

[0028] In the communication scheduling model, two types of messages are defined: the scheduling instruction packet and the feedback data packet. The former is sent by the master node and specifies the transmission delay of all slave nodes participating in the encirclement (the time from when a slave node receives the scheduling instruction packet to when it sends the feedback data packet) and the formation command information (information for guiding the movement and formation adjustment of the slave nodes); the latter is sent by the slave nodes and includes the position coordinates and motion state of the slave nodes themselves. Based on the above feedback information, the master node calculates and predicts the real-time dynamic azimuth of the slave nodes, thereby precisely scheduling the data transmission of the slave nodes.

[0029] Specifically, Figure 1 As shown in the flowchart of the communication scheduling method for underwater cluster collaborative encirclement according to an embodiment of the present application, as Figure 1 shown, the communication scheduling method for underwater cluster collaborative encirclement according to an embodiment of the present application includes the following steps: S101. Obtain the initial scheduling instruction packet and send it to each slave node so that each slave node generates a feedback data packet according to the initial scheduling instruction packet, where the scheduling instruction packet includes the channel access time and the scheduling maintenance period of each slave node.

[0030] As an embodiment, the scheduling instruction packet further includes formation command information, and the formation command information includes the expected movement positions corresponding to each slave node to dynamically adjust the network topology structure.

[0031] It should be noted that the transmission delay of the slave node refers to the time from when the slave node receives the scheduling instruction packet to when it sends the feedback data packet, and the scheduling maintenance period refers to the time interval between two consecutive transmissions of the scheduling instruction packet by the master node.

[0032] As an embodiment, each slave node generates a feedback data packet according to the initial scheduling instruction packet, including: each slave node decodes the received initial scheduling instruction packet to obtain the corresponding channel access time and expected movement position; each slave node moves according to the expected movement position and sends its own feedback data packet to the master node at the corresponding channel access time.

[0033] That is to say, as Figure 3 shown, the master node calculates the transmission delay, the current round of scheduling maintenance period, and the formation command information of each slave node; after encapsulating the above information, it is broadcast in the message type of the scheduling instruction packet; after receiving the scheduling instruction packet, the slave node transmits several feedback data packets to the master node after several transmission delays.

[0034] S102. Receive the feedback data packets sent by each slave node, where the feedback data packet includes the position information and motion state of the slave node itself.

[0035] It should be noted that the position information of the slave node itself is the geographical location coordinates, and the motion state refers to the real-time state information of the slave node moving in the underwater environment. For example, the moving speed and direction of the slave node, the distance and relative position between the slave node and the encirclement target, etc. This application does not make specific limitations on this.

[0036] S103. Calculate the corresponding information value according to the feedback data packet and its reception time to obtain the corresponding quantitative slot redundancy.

[0037] As an embodiment, calculating the corresponding information value according to the feedback data packet and its reception time to obtain the corresponding quantitative slot redundancy includes: starting timing before sending the scheduling instruction packet until the feedback data packets of each slave node are received and stopped, so as to obtain the propagation delay corresponding to each slave node; obtaining the information value corresponding to each slave node according to the propagation delay, and obtaining the corresponding quantitative slot redundancy according to the information value.

[0038] As a specific embodiment, as time goes by, underwater ocean currents and obstacles will cause deviations between the feedback information and the actual motion state of the slave node. Therefore, simply using feedback information for scheduling, the channel collision probability will inevitably increase. Thus, as shown in the following formula, by introducing the value of information (VOI) to quantify the reliability of the feedback data packet, through the quantitative calculation of slot redundancy, the channel collision probability can be further reduced and the channel utilization rate can be improved.

[0039]

[0040] Among them, represents the corresponding information value, represents the initial value of the information value, represents the end-to-end delay, that is, the propagation delay, represents the maximum effective time of the information, and represent the correction parameters.

[0041] It should be noted that when performing scheduling calculations, the closer the VOI is to the initial value , the more timely the feedback information of the slave node, and the higher the reliability of the information, and the less the required slot redundancy. When the VOI is the initial value , only the protection interval of needs to be used as the slot redundancy; when the VOI reaches the minimum value, the motion state of the slave node has become unreliable due to the long-term lack of update, and at this time, the maximum slot redundancy is given to it, where represents the maximum propagation distance of the underwater acoustic channel, that is, the maximum distance between the node and the master node, which depends on factors such as the underwater environment, the transmission power of the sonar, and the receiving sensitivity, represents the underwater acoustic rate. Using a linear relationship to complete the mapping, the following formula for slot redundancy is obtained:

[0042] where, represents the quantitative slot redundancy corresponding to the k-th slave node, represents the maximum slot redundancy, represents the minimum slot redundancy, represents the information value corresponding to the k-th slave node.

[0043] S104, use a genetic algorithm to generate the scheduling transmission order of the feedback data packets of each slave node, and obtain the channel access time of each slave node in the next round according to the quantitative slot redundancy.

[0044] As an embodiment, using a genetic algorithm to generate the scheduling transmission order of the feedback data packets of each slave node includes: initializing the sequence set composed of each slave node; constructing a fitness function to evaluate the transmission sequence overhead of each individual in the sequence set, so as to select a fixed number of elite sequence individuals into the next generation; performing crossover and mutation on the elite sequence individuals until the next generation sequence set is filled; calculating the average fitness of the next generation sequence set to obtain the overall mean square error according to the average fitness; calculating the dynamic mutation probability according to the overall mean square error; using the dynamic mutation probability to mutate all sequence individuals in the next generation sequence set, and so on, until the stop condition is met and then output the scheduling transmission order of the feedback data packets of each slave node.

[0045] It should be noted that the essence of VOI is information value, which can measure the effectiveness of the feedback information of the slave node. Different transmission sequences will affect the VOI and slot redundancy in the next scheduling: if the transmission order of a slave node is adjusted forward, then in the next scheduling calculation, its VOI will decrease accordingly. In the pursuit task, the master node always expects to obtain timely global node information (that is, as high a VOI as possible) for pursuit decision-making and scheduling calculation. To maximize the VOI of the information received by the master node, an improved genetic algorithm is proposed, which comprehensively considers the reliability of the feedback information of the cluster nodes and minimizes the frame length by optimizing the transmission sequence, thereby improving the throughput. The proposed improved genetic algorithm is as follows:

[0046] Specifically, consider a complete undirected graph G(N, a) with N cluster nodes. N is the set of nodes in the network, and N = {0, 1, 2, …, N}. Then the sequence optimization objective of the genetic algorithm is to minimize the frame length, and the optimization function is:

[0047] where c represents the underwater acoustic rate, represents the data packet length, represents the communication rate, represents the frame length of the i-th sequence individual in the sequence set of the t-th generation, is the distance between the master node and the first sending node, is the slot redundancy size of the k-th data node under the corresponding sequence. By performing a negative exponential mapping on the frame length, the fitness function of the i-th individual in the sequence set of the t-th generation can be obtained:

[0048] That is to say, the genetic algorithm first needs to complete the initialization of the sequence set. The initial set contains N random transmission sequences, and at the same time, it is evaluated based on the fitness function to calculate the overhead of all transmission sequences. During the iteration of the sequence set, a fixed number of excellent sequences with high fitness are directly selected into the next generation, and then the remaining sequences are generated using the crossover and mutation scheme shown in the above genetic algorithm, which ensures that sequences with higher fitness are selected into the next generation population set multiple times. Based on the adaptive scheme, the parent sequences in the crossover process are selected, that is, the sequences with the largest difference in fitness among the excellent sequences are selected. This method avoids inbreeding, optimizes the sequence set of the next generation, and then selects the two sequences with the largest difference in fitness among the remaining sequences to complete the crossover process to generate offspring sequences until the remaining sequences in the next generation set are empty.

[0049] After the genetic algorithm completes crossover and mutation, random mutation is introduced to achieve fast convergence. In the traditional genetic algorithm, the mutation probability is fixed throughout the evolution process. However, this application uses an adaptive mutation probability adjustment method based on the overall mean square deviation. The overall mean square deviation (Average Square Deviation, ASD) describes the specific differences within the set. The larger the ASD value, the greater the differences between the sequences in the set:

[0050]

[0051] where, represents the average fitness of the sequence set of the t-th generation, represents the fitness of the sequence individual of the t-th generation set, and N represents the total number of sequences in the set. The dynamic mutation probability Calculated by the following formula:

[0052] Wherein, represents a fixed mutation probability, represents the maximum fitness in the current set. The dynamic mutation probability is related to the mutation probability and ASD. When the ASD value decreases, will increase dynamically to promote the diversity of sequences within the set.

[0053] The initial set is subjected to multiple rounds of crossover mutation and iterative optimization until the stop condition is met, and then the final excellent sequence set can be obtained. Selecting the sequence with the smallest transmission overhead among them is the transmission sequence that meets the requirements. The genetic algorithm realizes the minimization of the frame length and improves the network throughput by imitating the mechanism of selection and inheritance in nature. At the same time, the potential parallelism of the genetic algorithm can simplify the complexity of the sequence optimization problem and reduce the requirements for actual deployed devices, and has good adaptability to the scenario of low channel utilization and limited energy consumption in the underwater unmanned capture cluster.

[0054] S105, calculate the cluster compactness and the maximum communication distance according to the feedback data packet, and obtain the scheduling maintenance period of the next round according to the cluster compactness and the maximum communication distance.

[0055] As a specific embodiment, in different stages of the capture task, a single scheduling can maintain multiple cycles in the manner shown by Figure 3 . The scheduling maintenance period affects the capture success rate and the energy consumption of the master node. High-frequency scheduling can increase the capture success rate, but it will correspondingly increase the energy consumption and reduce the working life of the master node. Therefore, as the capture task progresses, it is important to dynamically adjust the scheduling model maintenance period; adaptively adjust the scheduling maintenance period through the compactness and the communication distance :

[0056]

[0057] Wherein, represents the cluster compactness, represents the maximum communication distance, , represent the spatial coordinates of the cluster members, , represent the spatial coordinates of the capture target. The set of cluster member numbers is [0, n], and the master node number is always fixed at 0; the cluster compactness Quantify the dispersion degree of the cluster and the surrounded target, that is, the average distance of the cluster members (the master node and slave nodes together form the cluster) to the surrounded target \(d_{i,t}\). The communication distance is the maximum communication distance from each cluster member to the master node. Further, calculate the scheduling maintenance period through the normalized cluster compactness and the maximum communication distance :

[0058]

[0059] wherein represents the scheduling maintenance period of the next round, represents the normalization factor of the cluster compactness and the maximum communication distance, which is obtained according to the initial deployment range \(X\times Y\) of the cluster; both the cluster compactness and the maximum communication distance are signs of the surrounded stage. The cluster compactness represents the necessity of increasing the scheduling frequency in the later stage of the surrounded stage, and the maximum communication distance reflects the necessity of reducing the scheduling frequency in the early stage of the surrounded stage.

[0060] It should be noted that not long after the surrounded task starts, the cluster members are far from the surrounded target. At this time, the task of the cluster members is to approach the target, and only need to move forward in a general established direction, without the need for the master node to command and schedule frequently; and the slave nodes are also far from the master node, and the master node needs a large command node transmission power to complete a single scheduling communication. Therefore, it is necessary to increase the scheduling maintenance period, reduce the scheduling frequency, and reduce the energy consumption of the master node. As the surrounded stage progresses, the average distance between the cluster members and the surrounded target decreases, and it is necessary to reduce the scheduling maintenance period and command the slave nodes more precisely and frequently; at the same time, the communication distance also shows the same downward trend, which can increase the scheduling frequency while reducing the energy consumption of a single scheduling.

[0061] S106. Generate the scheduling instruction packet of the next round according to the channel access time of each slave node in the next round and the scheduling maintenance period of the next round for communication scheduling.

[0062] That is to say, the master node sends the scheduling instruction packet according to the calculated scheduling maintenance period and performs cyclic communication scheduling until the collaborative surrounded is finally completed.

[0063] In summary, according to the communication scheduling method for underwater cluster collaborative hunting in the embodiments of the present application, during the process of continuously tracking the hunting target by the master node, scheduling instruction packets are periodically sent outwards to command the channel access time and the movement destination location of the slave nodes. Among them, the scheduling instruction packets include the numbers and transmission delays of each slave node, which are used to determine the channel access timing of the slave nodes and the maintenance period of this scheduling, and the numbers and expected movement positions of each slave node, which are used to dynamically adjust the network topology; based on the feedback data packets received in this round of scheduling stage and their arrival times, calculate the propagation delays between the master node and each slave node, as well as the information value and quantitative time slot redundancy of the feedback data packets. The calculation of the propagation delay does not require the hunting cluster to achieve clock synchronization. Before sending the scheduling instruction packet, the master node starts timing, listens for the feedback data packets of each slave node, obtains the propagation delay corresponding to each slave node according to the time difference between the calculations, and further calculates the information value and quantitative time slot redundancy; based on the propagation delay and the information value corresponding to the feedback data packet, determine the transmission time slot optimization scheme for each slave node, and generate the data packet scheduling transmission order for each slave node accordingly. Among them, according to the information value and the scheduling maintenance period, through an improved genetic algorithm, determine the channel access time of each slave node under multiple scheduling maintenance periods; according to the network topology and the movement state of the slave nodes, calculate the cluster compactness and the maximum communication distance, quantify the cluster dispersion degree and the hunting task advancement stage, and determine the next scheduling maintenance period. Among them, the slave nodes listen for the scheduling instruction packets, match the decoded information with their own numbers to obtain the corresponding channel access time and movement destination location, and send feedback data packets at this channel access time. The feedback data packets include the current geographical location coordinates and movement state of the slave nodes themselves, which can determine the network topology of the current cluster network and the movement state of the slave nodes; thus, based on the feedback information, dynamically adjust the scheduling parameters to improve the support of the communication protocol for underwater cluster collaborative hunting communication, thereby improving the efficiency and success rate of the underwater cluster collaborative hunting task.

[0064] To implement the above embodiments, the embodiments of the present application also propose a communication scheduling device for underwater cluster collaborative hunting, as Figure 4 shown. The communication scheduling device for underwater cluster collaborative hunting includes: a sending module 10, a receiving module 20, a first calculation module 30, a processing module 40, a second calculation module 50, and a communication scheduling module 60.

[0065] Among them, the sending module 10 is used to obtain an initial scheduling instruction packet and send it to each slave node, so that each slave node can generate a feedback data packet according to the initial scheduling instruction packet. The scheduling instruction packet includes the channel access time and scheduling maintenance period of each slave node; the receiving module 20 is used to receive the feedback data packets sent by each slave node. The feedback data packet includes the position information and motion state of the slave node itself; the first calculation module 30 is used to calculate the corresponding information value according to the feedback data packet and its reception time to obtain the corresponding quantitative time slot redundancy; the processing module 40 is used to generate the scheduling transmission order of the feedback data packets of each slave node by using a genetic algorithm and obtain the channel access time of each slave node in the next round according to the quantitative time slot redundancy; the second calculation module 50 is used to calculate the cluster tightness and the maximum communication distance according to the feedback data packet and obtain the scheduling maintenance period in the next round according to the cluster tightness and the maximum communication distance; the communication scheduling module 60 is used to generate a scheduling instruction packet in the next round according to the channel access time of each slave node in the next round and the scheduling maintenance period in the next round for communication scheduling.

[0066] It should be noted that the above description and example of the communication scheduling method for underwater cluster cooperative hunting are also applicable to the communication scheduling device for underwater cluster cooperative hunting in this embodiment, and will not be elaborated here.

[0067] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can be in the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can be in the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0068] The present application is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram, and the combination of processes and / or blocks in the flowchart and / or block diagram can be realized by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate means for realizing the functions specified in Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0069] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to operate in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including an instruction means that implements the functions specified in one or more of the flows Figure 1 one or more of the flows and / or boxes Figure 1 specified in one or more of the boxes.

[0070] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, so that the instructions executed on the computer or other programmable apparatus provide steps for implementing the functions specified in one or more of the flows Figure 1 one or more of the flows and / or boxes Figure 1 specified in one or more of the boxes.

[0071] It should be noted that in the claims, any reference signs placed in parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The present application can be implemented by means of hardware including several different elements and by means of a suitably programmed computer. In a unit claim listing several means, several of these means can be embodied by one and the same item of hardware. The use of the words first, second, and third, etc. does not denote any order. These words can be interpreted as names.

[0072] Although the preferred embodiments of the present application have been described, additional changes and modifications can be made by those skilled in the art once they learn the basic inventive concept. Therefore, the appended claims are intended to be construed to include the preferred embodiments as well as all changes and modifications falling within the scope of the present application.

[0073] It is obvious that those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalent technologies, the present application is also intended to include these modifications and variations.

[0074] In the description of the present application, it should be understood that the terms "first" and "second" are used for descriptive purposes only and cannot be construed as indicating or implying relative importance or implicitly indicating the quantity of the indicated technical features. Thus, features defined with "first" and "second" may explicitly or implicitly include one or more of such features. In the description of the present application, "a plurality of" means two or more unless otherwise specifically defined.

[0075] In this application, unless otherwise clearly defined or limited, terms such as "installed", "connected", "joined", "fixed", etc. shall be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or integrated; it can be a mechanical connection or an electrical connection; it can be directly connected or indirectly connected through an intermediate medium, and it can be the communication inside two elements or the interaction relationship between two elements. For those of ordinary skill in the art, the specific meanings of the above terms in this application can be understood according to specific circumstances.

[0076] In this application, unless otherwise clearly defined or limited, the first feature being "on" or "under" the second feature can be that the first and second features are in direct contact, or the first and second features are indirectly in contact through an intermediate medium. Moreover, the first feature being "above", "over" and "on top of" the second feature can be that the first feature is directly above or obliquely above the second feature, or merely means that the first feature has a higher horizontal height than the second feature. The first feature being "under", "beneath" and "underneath" the second feature can be that the first feature is directly below or obliquely below the second feature, or merely means that the first feature has a lower horizontal height than the second feature.

[0077] In the description of this specification, the descriptions with reference to terms such as "an embodiment", "some embodiments", "examples", "specific examples", or "some examples", etc. mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of this application. In this specification, the schematic descriptions of the above terms should not be understood as necessarily referring to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples. In addition, without contradiction, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0078] Although the embodiments of this application have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting this application. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application.

Claims

1. A communication scheduling method for underwater cluster collaborative roundup, characterized in that: The underwater cluster includes a master node and multiple slave nodes, and the communication scheduling method includes the following steps: Acquire an initial scheduling instruction packet and send it to each slave node, so that each slave node generates a feedback data packet according to the initial scheduling instruction packet, wherein the scheduling instruction packet includes a channel access time and a scheduling maintenance period of each slave node; Receiving feedback data packets sent by each slave node, wherein the feedback data packets include the position information and motion status of the slave node itself; Calculating the corresponding information value according to the feedback data packet and its receiving time to obtain the corresponding quantitative time slot redundancy; Genetic algorithm is used to generate the transmission order of feedback data packets of each slave node, and the channel access time of each slave node in the next round is obtained according to the quantitative time slot redundancy; Calculating the cluster density and the maximum communication distance according to the feedback data packet, and obtaining the next round of scheduling maintenance period according to the cluster density and the maximum communication distance; A scheduling instruction packet for the next round is generated according to the channel access time of each slave node for the next round and the scheduling maintenance period for the next round, so as to perform communication scheduling.

2. The communication scheduling method for underwater cluster collaborative capture as claimed in claim 1, characterized in that: The scheduling instruction packet also includes formation command information, and the formation command information includes the expected movement position corresponding to each slave node to dynamically adjust the network topology structure.

3. The communication scheduling method for underwater cluster collaborative capture as claimed in claim 2, characterized in that: Each slave node generates a feedback data packet according to the initial scheduling instruction packet, including: Each slave node decodes the received initial scheduling instruction packet to obtain a corresponding channel access time and an expected motion position; Each slave node moves according to the expected movement position, and sends its own feedback data packet to the master node at the corresponding channel access time.

4. The communication scheduling method for underwater cluster collaborative capture as claimed in claim 1, characterized in that: Calculating the corresponding information value according to the feedback data packet and its receiving time to obtain the corresponding quantitative time slot redundancy includes: The timing starts before sending the scheduling instruction packet and stops when receiving the feedback data packet from each slave node, so as to obtain the propagation delay corresponding to each slave node; The information value corresponding to each slave node is obtained according to the propagation delay, and the corresponding quantitative time slot redundancy is obtained according to the information value.

5. The communication scheduling method for underwater cluster collaborative capture as claimed in claim 4, characterized in that: The information value corresponding to each slave node is obtained according to the following formula: in, Indicates the corresponding information value, represents the initial value of information value, represents the end-to-end delay, i.e., the propagation delay, Indicates the maximum effective time of the information. and Indicates the correction parameter.

6. The communication scheduling method for underwater cluster collaborative capture as claimed in claim 5, characterized in that: The quantitative time slot redundancy corresponding to each slave node is obtained according to the following formula: in, represents the quantitative time slot redundancy corresponding to the kth slave node, represents the maximum time slot redundancy, represents the minimum time slot redundancy, Indicates the information value corresponding to the kth slave node.

7. The communication scheduling method for underwater cluster collaborative capture as claimed in claim 1, characterized in that: Genetic algorithm is used to generate the transmission order of feedback data packets of each slave node, including: Initialize the sequence set composed of each slave node; A fitness function is constructed to evaluate the transmission sequence overhead of each individual in the sequence set so as to select a fixed number of elite sequence individuals into the next generation; Performing crossover mutation on the elite sequence individuals until the next generation sequence set is filled; Calculating the average fitness of the next generation sequence set to obtain a total mean square error according to the average fitness; Calculate the dynamic mutation probability according to the overall mean square error; All sequence individuals in the next generation sequence set are mutated using a dynamic mutation probability, and so on, until a stop condition is met, and then the transmission order of the feedback data packets of each slave node is output.

8. The communication scheduling method for underwater cluster collaborative capture as claimed in claim 1, characterized in that: The cluster density and maximum communication distance are calculated according to the following formula: in, represents the cluster compactness, Indicates the maximum communication distance, , represents the spatial coordinates of cluster members, , Represents the spatial coordinates of the target to be captured. The cluster member number set is [0,n], and the master node number is always fixed to 0.

9. The communication scheduling method for underwater cluster collaborative capture as claimed in claim 8, characterized in that: The next round of scheduling maintenance period is obtained according to the following formula: in, Indicates the next round of scheduling maintenance period, The normalization factor representing the cluster compactness and the maximum communication distance is obtained according to the initial deployment range X×Y of the cluster.

10. A communication scheduling device for underwater cluster collaborative capture, characterized in that: The underwater cluster includes a master node and a plurality of slave nodes, and the communication scheduling device includes: A sending module, used for acquiring an initial scheduling instruction packet and sending it to each slave node, so that each slave node generates a feedback data packet according to the initial scheduling instruction packet, wherein the scheduling instruction packet includes a channel access time and a scheduling maintenance period of each slave node; A receiving module, configured to receive feedback data packets sent by each slave node, wherein the feedback data packets include the position information and motion status of the slave node itself; A first calculation module, configured to calculate a corresponding information value according to the feedback data packet and its receiving time, so as to obtain a corresponding quantitative time slot redundancy; A processing module, used for generating a transmission order of feedback data packets of each slave node by using a genetic algorithm, and obtaining a channel access time of each slave node in the next round according to the quantitative time slot redundancy; A second calculation module, used to calculate the cluster density and the maximum communication distance according to the feedback data packet, and obtain the next round of scheduling maintenance period according to the cluster density and the maximum communication distance; The communication scheduling module is used to generate a scheduling instruction packet for the next round according to the channel access time of each slave node in the next round and the scheduling maintenance period of the next round, so as to perform communication scheduling.

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