Underwater acoustic communication network routing method for dynamically optimizing communication resources

Abstract

The invention belongs to the field of underwater acoustic routing protocols, and relates to an underwater acoustic communication network routing method for dynamically optimizing communication resources. The underwater acoustic communication network comprises a source node, a destination node and a plurality of relay nodes, and the method comprises the following steps: step 1) the source node initiates initialization of the underwater acoustic communication network, and each relay node constructs a local topology table through exchange of metadata packets; 2) the sending node determines a forwarding candidate set according to the position information and the residual energy of the neighbor nodes; step 3) the sending node selects the relay node with the highest forwarding priority in the forwarding candidate set as the optimal relay; step 4) the sending node performs communication resource optimization to obtain communication parameter configuration; 5) the sending node sends a data packet to the optimal relay node according to the configured communication parameters; 6) judging whether the receiving node is a destination node or not, and if yes, ending; and if not, repeating the steps 2) to 5) until the receiving node is the destination node.

Description

Technical Field

[0001] The present invention relates to the fields of underwater acoustic communication networks and underwater acoustic routing protocols, and in particular to an underwater acoustic communication network routing method for dynamically optimizing communication resources. Background Art

[0002] With the growing global demand for maritime defense and security, marine resource exploration and development, and marine environmental monitoring, there is an urgent need for reliable underwater information transmission. Traditional point-to-point underwater acoustic communication is no longer able to meet the requirements of collaborative node operations, making underwater acoustic communication networking a research hotspot for marine informatization. However, limited underwater acoustic communication resources, time-varying channels, and dynamic network topology changes present multiple challenges in networking protocol design. Achieving efficient utilization and dynamic optimization of network resources within these constraints has become a key challenge in underwater acoustic communication networking.

[0003] Under the dual constraints of resources and dynamics, the design of underwater acoustic communication routing protocols faces severe challenges. Although a large amount of research has been devoted to optimizing the performance of routing protocols, most of this work focuses on a single objective. For example, energy-optimized protocols sacrifice transmission timeliness in order to extend network life, resulting in increased end-to-end latency for data transmission. Multipath routing improves reliability through redundant forwarding, but the collaboration of multiple nodes incurs additional energy consumption. In addition, existing routing protocols have poor adaptability in dynamically changing network environments and find it difficult to make effective routing decisions based on real-time changes in network status. Therefore, designing a multi-objective optimized routing that takes into account both resource efficiency and dynamic adaptability has become a breakthrough in achieving reliable transmission of underwater acoustic communications. Summary of the Invention

[0004] The purpose of the present invention is to overcome the defects of the prior art and propose an underwater acoustic communication network routing method with dynamic optimization of communication resources.

[0005] In view of this, the present invention proposes an underwater acoustic communication network routing method for dynamically optimizing communication resources. The underwater acoustic communication network includes: a source node, a destination node, and multiple relay nodes. The method includes:

[0006] Step 1) The source node initiates the initialization of the underwater acoustic communication network, and each relay node builds a local topology table by exchanging metadata packets;

[0007] Step 2) The sending node determines the forwarding candidate set based on the location information and remaining energy of the neighboring nodes;

[0008] Step 3) The sending node selects the relay node with the highest forwarding priority from the forwarding candidate set as the optimal relay;

[0009] Step 4) The sending node optimizes communication resources to obtain communication parameter configuration;

[0010] Step 5) The sending node sends the data packet to the optimal relay node according to the configured communication parameters;

[0011] Step 6) Determine whether the receiving node is the destination node: if it is the destination node, end; if not, repeat steps 2) to 5) until the receiving node is the destination node.

[0012] Preferably, both the source node and the relay node can be sending nodes.

[0013] Preferably, the step 1) comprises:

[0014] The source node broadcasts a metadata packet: the metadata packet includes: packet type, node ID, timestamp, geographic location and remaining energy. After receiving the broadcast metadata packet, each relay node within the communication range builds a local topology table and maintains topology information including node location and energy status.

[0015] Preferably, the step 2) comprises:

[0016] The sending node determines the forwarding candidate set candidateSet based on the location information and remaining energy of the neighboring nodes:

[0017] candidateSet=Subset1∩Subset2

[0018] Among them, Subset1 is the set of neighbor nodes that are closer to the destination node when the sending node selects the next hop, and Subset2 is the subset of nodes in the candidate set that meet the energy constraint. The definitions of the two are as follows:

[0019]

[0020] Among them, Neighbor i is the sending node n i The neighbor set of l jd and l id Represents node n j and node n i The distance to the destination node, For node n j The remaining energy, For node n j The initial energy.

[0021] Preferably, the step 3) comprises:

[0022] The node with the highest forwarding priority in the candidate forwarding set is selected as the next hop node. The forwarding priority W is:

[0023]

[0024] Among them, β is the distance weight, D f is the distance factor, α is the energy weight, and satisfies the following formula:

[0025]

[0026] Among them, p sent is the number of packets sent, p total The total number of packets to be sent.

[0027] Preferably, the step 4) comprises:

[0028] A multi-objective resource optimization model is constructed, incorporating modulation scheme, subcarrier spacing, guard interval, and transmission power into the optimization framework. The goal is to minimize energy consumption, reduce end-to-end latency, and improve bandwidth utilization. The communication resource optimization problem is formulated as a multi-objective optimization problem.

[0029] The NSGA-II algorithm is used to solve the multi-objective optimization problem. The Pareto optimal solution set is generated through non-dominated sorting and hybrid elite retention strategies. The best compromise solution is selected in combination with the ideal point method to achieve communication resource optimization and obtain communication parameter configuration.

[0030] Preferably, the multi-objective optimization problem is:

[0031] Based on the given node numbers i and j, the maximum power allowed by the underwater acoustic communication system is P s,max , node n j The minimum power that can be correctly received is P s,min , bandwidth is B, the maximum communication distance of the node is d max , the bit error rate meets the threshold BER th ;

[0032] With the goal of minimizing energy consumption, reducing end-to-end delay and improving bandwidth utilization, it obeys the following formula:

[0033] P s,min ≤P s,ij ≤P s,max

[0034]

[0035] Among them, v ij For node n i and node n j The relative moving speed, c is the speed of sound, f i0 is the frequency of the first subcarrier, is node n j Received bit error rate;

[0036] Get the communication parameter configuration, including: select the best relay node number j from the candidate relay node set N of the current node * , node n i To node n j The transmission power P s,ij , subcarrier spacing Δf ij , protection interval T g,ij , node n i To node n j The modulation method used when sending data Where M{2,4,8,16,64} is the set of available modulation scheme candidates.

[0037] Compared with the prior art, the advantages of the present invention are:

[0038] 1. The present invention provides an underwater acoustic communication network routing method ROAR for dynamic optimization of communication resources, which realizes the coordinated optimization of resource efficiency and dynamic adaptability;

[0039] 2. We propose an energy-aware and distance-oriented relay selection strategy that comprehensively considers the remaining energy of the node and the distance to the destination node to achieve energy consumption balance, improve network lifespan and packet delivery rate;

[0040] 3. A multi-objective resource optimization model was constructed, incorporating modulation schemes, subcarrier spacing, guard intervals, and transmission power into the optimization framework. This model aims to minimize energy consumption, reduce end-to-end latency, and improve bandwidth utilization. Compared to single-objective optimization schemes, this model achieves a better balance across multiple performance dimensions.

[0041] 4. Use the NSGA-II algorithm to solve multi-objective optimization problems. Generate a Pareto optimal solution set through non-dominated sorting and a hybrid elite retention strategy, and combine it with the ideal point method to select the best compromise solution, making the resource allocation strategy adaptive to the network status. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 This is a flow chart of an underwater acoustic communication network routing method for dynamically optimizing communication resources in an embodiment;

[0043] Figure 2 is a graph showing the change of the objective function value with the number of iterations in the embodiment;

[0044] Figure 3 The performance comparison of the present invention with the ER protocol and the DR protocol in terms of average packet energy consumption in the embodiment is as follows;

[0045] Figure 4 The performance comparison of the present invention with the ER protocol and the DR protocol in terms of average end-to-end delay in the embodiment;

[0046] Figure 5 The performance comparison of the present invention with the ER protocol and the DR protocol in terms of packet delivery rate in the embodiment;

[0047] Figure 6 is a performance comparison of the present invention with QELAR and RCAR in terms of average packet energy consumption in the embodiment;

[0048] Figure 7 FIG. 1 is a performance comparison of the present invention with QELAR and RCAR in terms of packet delivery rate in the embodiments. DETAILED DESCRIPTION

[0049] The present invention provides an underwater acoustic communication network routing method for dynamically optimizing communication resources, which comprises the following steps:

[0050] 1. The source node initiates the initialization of the underwater acoustic communication network, and each node builds a local topology table by exchanging metadata packets;

[0051] 2. The sending node determines the forwarding candidate set based on the location information and remaining energy of the neighboring nodes;

[0052] (2.1) Filter out the forward-moving subset Subset1:

[0053]

[0054] Among them, the forward subset is the set of neighbor nodes that are closer to the destination node when the sending node selects the next hop. i is the sending node n i The neighbor set of l jd and l id Represents node n j and node n i The distance to the destination node.

[0055] (2.2) Filter out the subset Subset2 that meets the energy constraint:

[0056]

[0057] in, For node n j The remaining energy, For node n j The initial energy.

[0058] (2.3) The forwarding candidate set is the intersection of Subset1 and Subset2:

[0059] candidateSet=Subset1∩Subset2

[0060] Among them, candidateSet is the final determined candidate forwarding set of the current node.

[0061] 3. The sending node selects the node with the highest forwarding priority in the forwarding candidate set as the optimal relay;

[0062] (3.1) Calculate the forwarding priority of the node in the forwarding candidate set. The calculation formula is:

[0063]

[0064] Among them, α is the energy weight, β is the distance weight, D f is the distance factor. The energy weight α is defined as:

[0065]

[0066] Among them, p sent is the number of packets sent, p total The total number of packets to be sent.

[0067] (3.2) The node with the highest forwarding priority is selected as the optimal relay node.

[0068] 4. The sending node optimizes communication resources to obtain communication parameter settings;

[0069] (4.1) A multi-objective resource optimization model was constructed, incorporating modulation scheme, subcarrier spacing, guard interval, and transmission power into the optimization framework, with the goal of minimizing energy consumption, reducing end-to-end delay, and improving bandwidth utilization. The communication resource optimization problem is formulated as a multi-objective optimization problem:

[0070] Given:i,j,P s,min ,P s,max ,B,d max ,BER th

[0071] Find:

[0072] Minimize:{f1,f2,f3}

[0073] Subject to:P s,min ≤P s,ij ≤P s,max

[0074]

[0075]

[0076] Among them, i and j are node numbers, P s,maxis the maximum power allowed by the underwater acoustic communication system, P s,min For node n j The minimum power that can be correctly received, B is the bandwidth, d max is the maximum communication distance of the node, BER th Is the bit error rate should meet the threshold, P s,ij is node n i To node n j The transmission power, Δf ij is the subcarrier spacing, T g,ij is the guard interval, is node n i To node n j The modulation mode selected when sending data, M{2,4,8,16,64} is the set of available modulation mode candidates, f1 is the function with the goal of reducing energy consumption, f2 is the function with the goal of improving bandwidth utilization, f3 is the function with the goal of reducing latency, v ij For node n i and node n j The relative moving speed, c is the speed of sound, f i0 is the frequency of the first subcarrier, is node n j Received bit error rate.

[0077] (4.2) The NSGA-II algorithm is used to solve the multi-objective optimization problem. The Pareto optimal solution set is generated through non-dominated sorting and hybrid elite retention strategies, and the best compromise solution is selected in combination with the ideal point method.

[0078] 5. The sending node sends the data packet to the optimal relay node according to the configured communication parameters;

[0079] 6. Determine whether the receiving node is the destination node: if it is the destination node, end; if not, repeat steps 2 to 5 until the receiving node is the destination node.

[0080] The technical solution of the present invention is described in detail below with reference to the accompanying drawings and embodiments.

[0081] Example 1

[0082] The embodiment of the present invention proposes an underwater acoustic communication network routing method for dynamically optimizing communication resources.

[0083] refer to Figure 1 The method of the present invention comprises the following steps:

[0084] 1. The source node initiates the initialization of the underwater acoustic communication network, and each node builds a local topology table by exchanging metadata packets;

[0085] 2. The sending node determines the forwarding candidate set based on the location information and remaining energy of the neighboring nodes;

[0086] 3. The sending node selects the node with the highest forwarding priority in the forwarding candidate set as the optimal relay;

[0087] 4. The sending node optimizes communication resources to obtain communication parameter settings;

[0088] 5. The sending node sends the data packet to the optimal relay node according to the configured communication parameters;

[0089] 6. Determine whether the receiving node is the destination node: if it is the destination node, end; if not, repeat steps 2 to 5 until the receiving node is the destination node.

[0090] Specifically:

[0091] 1. Initialize the network

[0092] The underwater acoustic communication network consists of a source node, a destination node, and multiple relay nodes. The relay nodes are randomly distributed in a 10km*10km*5km underwater three-dimensional space. Information is generated by the source node and forwarded hop-by-hop to the destination node via the relay nodes. Network topology information is constructed through metadata exchange: each node broadcasts a metadata packet containing information such as packet type, node ID, timestamp, geographic location, and remaining energy. Neighboring nodes within communication range receive the broadcast packet and update their local topology table to maintain topology information including node location and energy status. The parameter settings are shown in Table 1:

[0093] Table 1 Simulation parameter settings

[0094]

[0095] 2. Determine the forwarding candidate set

[0096] The steps for this section are as follows:

[0097] (2.1) Filter out the forward-moving subset Subset1:

[0098]

[0099] Among them, Neighbor i is node n i The neighbor set of l jd and l id Represents node n j and node n i The distance to the destination node.

[0100] (2.2) Filter out the subset Subset2 that meets the energy constraint:

[0101]

[0102] in, For node n j The remaining energy, For node n j The initial energy.

[0103] (2.3) The forwarding candidate set is the intersection of Subset1 and Subset2:

[0104] candidateSet=Subset1∩Subset2

[0105] Among them, candidateSet is the final determined candidate forwarding set of the current node.

[0106] 3. Select the best relay

[0107] The steps for this section are as follows:

[0108] (3.1) Calculate the forwarding priority of the node in the forwarding candidate set. The calculation formula is:

[0109]

[0110] Among them, α is the energy weight, β is the distance weight, D f is the distance factor. The energy weight α is defined as:

[0111]

[0112] Among them, p sent is the number of packets sent, p total The total number of packets to be sent.

[0113] (3.2) The node with the highest forwarding priority is selected as the optimal relay node.

[0114] 4. Communication resource optimization to obtain communication parameter settings

[0115] The steps for this section are as follows:

[0116] (4.1) A multi-objective resource optimization model was constructed, incorporating modulation scheme, subcarrier spacing, guard interval, and transmission power into the optimization framework, with the goal of minimizing energy consumption, reducing end-to-end delay, and improving bandwidth utilization. The communication resource optimization problem is formulated as a multi-objective optimization problem:

[0117] Given:i,j,P s,min ,P s,max ,B,d max ,BER th

[0118] Find:

[0119] Minimize:{f1,f2,f3}

[0120] Subject to:P s,min ≤P s,ij ≤P s,max

[0121]

[0122] Among them, i and j are node numbers, P s,max is the maximum power allowed by the underwater acoustic communication system, P s,min For node n j The minimum power that can be correctly received, B is the bandwidth, d max is the maximum communication distance of the node, BER th Is the bit error rate should meet the threshold, P s,ij is node n i To node n j The transmission power, Δf ij is the subcarrier spacing, T g,ij is the guard interval, is node n i To node n j The modulation mode selected when sending data, M{2,4,8,16,64} is the set of available modulation mode candidates, f1 is the function with the goal of reducing energy consumption, f2 is the function with the goal of improving bandwidth utilization, f3 is the function with the goal of reducing latency, v ij For node n i and node n j The relative moving speed, c is the speed of sound, f i0 is the frequency of the first subcarrier, is node n j Received bit error rate.

[0123] (4.2) The NSGA-II algorithm is used to solve the multi-objective optimization problem. The Pareto optimal solution set is generated through non-dominated sorting and hybrid elite retention strategies, and the best compromise solution is selected in combination with the ideal point method.

[0124] 5. The sending node sends the data packet to the optimal relay node according to the configured communication parameters;

[0125] 6. Determine whether the receiving node is the destination node: if it is the destination node, end; if not, repeat steps 2 to 5 until the receiving node is the destination node.

[0126] Figure 2It is a curve diagram of the objective function value changing with the number of iterations in the embodiment, which shows that the NSGA-II algorithm can effectively reduce the objective function value.

[0127] Figure 3 The performance of the present invention in the embodiment is compared with the ER protocol and the DR protocol in terms of average packet energy consumption. From the simulation results, it can be seen that ROAR always maintains the lowest energy consumption, indicating that its optimization direction can effectively reduce energy consumption and show good adaptability under different network scales.

[0128] Figure 4 This is a performance comparison of the present invention with the ER protocol and the DR protocol in terms of average end-to-end delay in the embodiment. ROAR can maintain a low end-to-end delay under different network scales.

[0129] Figure 5 The performance comparison of the present invention with the ER protocol and the DR protocol in terms of packet delivery rate in the embodiments shows that at different network scales, the packet delivery rate of ROAR is consistently higher than that of ER and DR. This is mainly attributed to the fact that ROAR selects individuals with optimal energy consumption, latency, and bandwidth utilization as ideal individuals, thereby achieving more balanced resource allocation among multiple performance indicators.

[0130] Figure 6 3 is a performance comparison of the present invention with QELAR and RCAR in terms of average packet energy consumption in the embodiment. As can be seen from the figure, the average packet energy consumption of ROAR is always lower than that of QELAR and RCAR, indicating that ROAR has a clear advantage in energy efficiency.

[0131] Figure 7 The performance comparison of the present invention with QELAR and RCAR in terms of packet delivery rate in the embodiment shows that the delivery rate of ROAR is significantly higher than that of the other two protocols, indicating that ROAR can more effectively ensure the successful transmission of data.

[0132] Finally, it should be noted that the above embodiments are intended only to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions to the technical solutions of the present invention do not depart from the spirit and scope of the technical solutions of the present invention and are intended to be encompassed by the claims of the present invention.

Claims

1. A method for routing underwater acoustic communication networks with dynamic optimization of communication resources, the underwater acoustic communication network comprising: A source node, a destination node, and multiple relay nodes, the method comprising: Step 1) The source node initiates the initialization of the underwater acoustic communication network, and each relay node builds a local topology table by exchanging metadata packets; Step 2) The sending node determines the forwarding candidate set based on the location information and remaining energy of the neighboring nodes; Step 3) The sending node selects the relay node with the highest forwarding priority from the forwarding candidate set as the optimal relay; Step 4) The sending node optimizes communication resources to obtain communication parameter configuration; Step 5) The sending node sends the data packet to the optimal relay node according to the configured communication parameters; Step 6) Determine whether the receiving node is the destination node: if it is the destination node, end; if not, repeat steps 2) to 5) until the receiving node is the destination node.

2. The underwater acoustic communication network routing method for dynamic optimization of communication resources according to claim 1 is characterized in that: Both the source node and the relay node can be sending nodes.

3. The underwater acoustic communication network routing method for dynamic optimization of communication resources according to claim 1 is characterized in that: The step 1) comprises: The source node broadcasts a metadata packet: the metadata packet includes: packet type, node ID, timestamp, geographic location and remaining energy. After receiving the broadcast metadata packet, each relay node within the communication range builds a local topology table and maintains topology information including node location and energy status.

4. The underwater acoustic communication network routing method for dynamic optimization of communication resources according to claim 1 is characterized in that: The step 2) comprises: The sending node determines the forwarding candidate set candidateSet based on the location information and remaining energy of the neighboring nodes: candidateSet=Subset1∩Subset2 Among them, Subset1 is the set of neighbor nodes that are closer to the destination node when the sending node selects the next hop, and Subset2 is the subset of nodes in the candidate set that meet the energy constraint. The definitions of the two are as follows: Among them, Neighbor i is the sending node n i The neighbor set of l jd and l id Represents node n j and node n i The distance to the destination node, For node n j The remaining energy, For node n j The initial energy.

5. The underwater acoustic communication network routing method for dynamic optimization of communication resources according to claim 1 is characterized in that: The step 3) comprises: The node with the highest forwarding priority in the candidate forwarding set is selected as the next hop node. The forwarding priority W is: Among them, β is the distance weight, D f is the distance factor, α is the energy weight, and satisfies the following formula: Among them, p sent is the number of packets sent, p total The total number of packets to be sent.

6. The underwater acoustic communication network routing method for dynamic optimization of communication resources according to claim 1 is characterized in that: The step 4) comprises: A multi-objective resource optimization model is constructed, incorporating modulation scheme, subcarrier spacing, guard interval, and transmission power into the optimization framework. The goal is to minimize energy consumption, reduce end-to-end latency, and improve bandwidth utilization. The communication resource optimization problem is formulated as a multi-objective optimization problem. The NSGA-II algorithm is used to solve the multi-objective optimization problem. The Pareto optimal solution set is generated through non-dominated sorting and hybrid elite retention strategies. The best compromise solution is selected in combination with the ideal point method to achieve communication resource optimization and obtain communication parameter configuration.

7. The underwater acoustic communication network routing method for dynamic optimization of communication resources according to claim 6 is characterized in that: The multi-objective optimization problem is: Based on the given node numbers i and j, the maximum power allowed by the underwater acoustic communication system is P s,max , node n j The minimum power that can be correctly received is P s,min , bandwidth is B, the maximum communication distance of the node is d max , the bit error rate meets the threshold BER th ; With the goal of minimizing energy consumption, reducing end-to-end delay and improving bandwidth utilization, it obeys the following formula: P s,min ≤P s,ij ≤P s,max Among them, v ij For node n i and node n j The relative moving speed, c is the speed of sound, f i0 is the frequency of the first subcarrier, is node n j Received bit error rate; Get the communication parameter configuration, including: select the best relay node number j from the candidate relay node set N of the current node * , node n i To node n j The transmission power P s,ij , subcarrier spacing Δf ij , protection interval T g,ij , node n i To node n j The modulation method used when sending data Where M{2,4,8,16,64} is the set of available modulation scheme candidates.

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