A routing method for a water acoustic communication network with dynamic optimization of communication resources

Abstract

The application belongs to the field of underwater acoustic routing protocol, and relates to a kind of underwater acoustic communication network routing method of dynamic optimization of communication resource.The underwater acoustic communication network includes a source node, a destination node and multiple relay nodes, and the method includes the following steps: step 1) the source node initiates the initialization of the underwater acoustic communication network, and each relay node constructs a local topology table through the exchange of metadata packets;step 2) the sending node determines a forwarding candidate set according to the position information and 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;step 5) the sending node sends data packets to the optimal relay node according to the configured communication parameters;step 6) it is judged whether the receiving node is the destination node: if it is the destination node, the process is ended;if not, steps 2) to 5) are repeated until the receiving node is the destination node.

Description

Technical Field

[0001] This invention relates to the fields of underwater acoustic communication networks and underwater acoustic routing protocols, and specifically to a routing method for underwater acoustic communication networks with dynamic optimization of communication resources. Background Technology

[0002] With the increasing demands of countries worldwide for maritime defense and security, marine resource exploration and development, and marine environmental monitoring, there is an urgent need for a reliable means of underwater information transmission. Traditional point-to-point underwater acoustic communication can no longer meet the requirements of collaborative operations among node groups; therefore, underwater acoustic communication networking technology has become a research hotspot in marine informatization. However, the limited resources, time-varying channels, and dynamic changes in network topology of underwater acoustic communication present multiple challenges in network protocol design. How to achieve efficient utilization and dynamic optimization of network resources under these constraints has become a key difficulty in underwater acoustic communication networking.

[0003] Under the dual constraints of resource efficiency and dynamic nature, the design of underwater acoustic communication routing protocols faces significant challenges. Although extensive research has focused on optimizing routing protocol performance, most work concentrates on a single objective. For example, energy-optimized protocols sacrifice transmission timeliness to extend network lifetime, leading to increased end-to-end data transmission latency. Multipath routing improves reliability through redundant forwarding, but multi-node coordination generates additional energy consumption. Furthermore, existing routing protocols exhibit poor adaptability in dynamically changing network environments, struggling to make effective routing decisions based on real-time changes in network conditions. Therefore, designing a multi-objective optimized route that balances resource efficiency and dynamic adaptability has become a breakthrough for achieving reliable underwater acoustic communication transmission. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of the prior art and to propose a routing method for underwater acoustic communication networks with dynamic optimization of communication resources.

[0005] In view of this, the present invention proposes a routing method for underwater acoustic communication networks with dynamic optimization of 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 constructs a local topology table by exchanging metadata packets;

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

[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 the communication parameter configuration;

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

[0011] Step 6) Determine if the receiving node is the destination node: If it is the destination node, end; otherwise, 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, step 1) includes:

[0014] Source node broadcast metadata: The metadata includes: packet type, node ID, timestamp, geographical location and remaining energy. Each relay node within the communication range receives the broadcast metadata and constructs a local topology table to maintain topology information including node location and energy status.

[0015] Preferably, step 2) includes:

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

[0017] candidateSet=Subset1∩Subset2

[0018] Where Subset1 is the set of neighboring 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 satisfy the energy constraint. The definitions of the two are as follows:

[0019]

[0020] Among them, Neighbor i It is the sending node n i The set of neighbors, l jd and l id Representing node n respectively j and node n i Distance to the destination node For node n j The remaining energy, For node n j The initial energy.

[0021] Preferably, step 3) includes:

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

[0023]

[0024] Where β is the distance weight, D f Let α be the distance factor and α be the energy weight, satisfying the following equation:

[0025]

[0026] Where, p sent p represents the number of data packets already sent. total The number of all data packets to be sent.

[0027] Preferably, step 4) includes:

[0028] A multi-objective resource optimization model is constructed, which incorporates 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 thus expressed as a multi-objective optimization problem.

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

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

[0031] Given node indices i and j, the maximum allowable power of the underwater acoustic communication system is P. s,max Node n j The minimum power that can be correctly received is P s,min The bandwidth is B, and the maximum communication distance between nodes is d. max The bit error rate meets the threshold BER. th ;

[0032] The goal is to minimize energy consumption, reduce end-to-end latency, and improve bandwidth utilization, which follows the 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 speed of movement, where c is the speed of sound, f i0 The frequency of the first subcarrier. It is node n j The received bit error rate;

[0036] Obtain the communication parameter configuration, including: selecting the optimal relay node number j from the candidate relay node set N of the current node. * Node n i to node n j Transmit power P s,ij Subcarrier spacing Δf ij Protection interval T g,ij Node n i To node n j Modulation method selected when transmitting 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. This invention provides a routing method ROAR for underwater acoustic communication networks that dynamically optimizes communication resources, achieving synergistic optimization of resource efficiency and dynamic adaptability;

[0039] 2. A relay selection strategy based on energy awareness and distance orientation is proposed, which comprehensively considers the remaining energy of the node and the distance to the destination node to achieve energy balance, improve network lifetime and packet delivery rate;

[0040] 3. A multi-objective resource optimization model was constructed, which incorporates 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. Compared with single-objective optimization schemes, it achieves a better balance in multiple performance dimensions.

[0041] 4. The NSGA-II algorithm is used to solve multi-objective optimization problems. A Pareto optimal solution set is generated through non-dominated sorting and a hybrid elite retention strategy, and the best compromise solution is selected by combining the ideal point method, enabling the resource allocation strategy to adapt to the network state. Attached Figure Description

[0042] Figure 1 This is a flowchart of a routing method for underwater acoustic communication network with dynamic optimization of communication resources in one embodiment;

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

[0044] Figure 3 This embodiment compares the performance of the present invention with the ER and DR protocols in terms of average packet power consumption.

[0045] Figure 4 This embodiment compares the performance of the present invention with the ER and DR protocols in terms of average end-to-end latency.

[0046] Figure 5 This embodiment compares the performance of the present invention with the ER and DR protocols in terms of packet delivery rate.

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

[0048] Figure 7 This embodiment compares the performance of the present invention with that of QELAR and RCAR in terms of package delivery rate. Detailed Implementation

[0049] This invention discloses a routing method for underwater acoustic communication networks with dynamic optimization of communication resources, comprising 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 of its neighboring nodes and its remaining energy;

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

[0053]

[0054] The forward subset is the set of neighboring nodes that are closer to the destination node when the sending node selects its next hop. i It is the sending node n i The set of neighbors, l jd and l id Representing node n respectively j and node n i Distance to the destination node.

[0055] (2.2) Select the subset Subset2 that satisfies 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] Wherein, candidateSet is the final set of candidate forwarding nodes for the current node.

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

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

[0063]

[0064] Where α is the energy weight, β is the distance weight, and D f The distance factor is denoted by α. The energy weight α is defined as follows:

[0065]

[0066] Where, p sent p represents the number of data packets already sent. total The number of all data packets to be sent.

[0067] (3.2) Select the node with the highest forwarding priority 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 objectives 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] Where i and j are node indices, P s,maxP is the maximum power allowed for an underwater acoustic communication system. s,min For node n j The minimum power that can be correctly received, where B is the bandwidth and d is the minimum power that can be correctly received. max BER represents the maximum communication distance between nodes. th The bit error rate should meet the threshold, P. s,ij It is node n i to node n j The transmit power, Δf ij It is the subcarrier spacing, T g,ij It is a protective interval. It is node n i To node n j The modulation scheme selected when transmitting data, M{2,4,8,16,64} is the set of available modulation scheme candidates, f1 is a function aimed at reducing power consumption, f2 is a function aimed at improving bandwidth utilization, f3 is a function aimed at reducing latency, and v ij For node n i and node n j The relative speed of movement, where c is the speed of sound, f i0 The frequency of the first subcarrier. It is node n j The received bit error rate.

[0077] (4.2) The NSGA-II algorithm is used to solve the multi-objective optimization problem. Pareto optimal solution set is generated by non-dominated sorting and mixed elite retention strategy, and the best compromise solution is selected by combining the ideal point method.

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

[0079] 6. Determine if the receiving node is the destination node: If it is the destination node, end; otherwise, repeat steps 2 to 5 until the receiving node is the destination node.

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

[0081] Example 1

[0082] Embodiments of the present invention propose a routing method for underwater acoustic communication networks with dynamic optimization of communication resources.

[0083] refer to Figure 1 The flowchart of the present invention shows that the method includes 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 of its neighboring nodes and its remaining energy;

[0086] 3. The sending node selects the node with the highest forwarding priority from 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 data packets to the optimal relay node according to the configured communication parameters;

[0089] 6. Determine if the receiving node is the destination node: If it is the destination node, end; otherwise, 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 one source node, one destination node, and multiple relay nodes. The relay nodes are distributed across a 10km x 10km x 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, geographical location, and remaining energy. Neighboring nodes within the communication range receive the broadcast packet and update their local topology table, maintaining topology information including node location and energy status. 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 It is node n i The set of neighbors, l jd and l id Representing node n respectively j and node n i Distance to the destination node.

[0100] (2.2) Select the subset Subset2 that satisfies 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] Wherein, candidateSet is the final set of candidate forwarding nodes for the current node.

[0106] 3. Select the optimal relay

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

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

[0109]

[0110] Where α is the energy weight, β is the distance weight, and D f The distance factor is denoted by α. The energy weight α is defined as follows:

[0111]

[0112] Where, p sent p represents the number of data packets already sent. total The number of all data packets to be sent.

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

[0114] 4. Communication resource optimization yields 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 objectives 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] Where i and j are node indices, P s,max P is the maximum power allowed for an underwater acoustic communication system. s,min For node n j The minimum power that can be correctly received, where B is the bandwidth and d is the minimum power that can be correctly received. max BER represents the maximum communication distance between nodes. th The bit error rate should meet the threshold, P. s,ij It is node n i to node n j The transmit power, Δf ij It is the subcarrier spacing, T g,ij It is a protective interval. It is node n i To node n j The modulation scheme selected when transmitting data, M{2,4,8,16,64} is the set of available modulation scheme candidates, f1 is a function aimed at reducing power consumption, f2 is a function aimed at improving bandwidth utilization, f3 is a function aimed at reducing latency, and v ij For node n i and node n j The relative speed of movement, where c is the speed of sound, f i0 The frequency of the first subcarrier. It is node n j The received bit error rate.

[0123] (4.2) The NSGA-II algorithm is used to solve the multi-objective optimization problem. Pareto optimal solution set is generated by non-dominated sorting and mixed elite retention strategy, and the best compromise solution is selected by combining the ideal point method.

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

[0125] 6. Determine if the receiving node is the destination node: If it is the destination node, end; otherwise, repeat steps 2 to 5 until the receiving node is the destination node.

[0126] Figure 2The graph shown in the example illustrates how the objective function value changes with the number of iterations, demonstrating that the NSGA-II algorithm can effectively reduce the objective function value.

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

[0128] Figure 4 This embodiment compares the performance of the present invention with the ER and DR protocols in terms of average end-to-end latency. ROAR can maintain low end-to-end latency under different network scales.

[0129] Figure 5 In this embodiment, the performance of the present invention compared with the ER and DR protocols in terms of packet delivery rate is shown. Under different network scales, the packet delivery rate of ROAR is always higher than that of ER and DR. This is mainly attributed to the fact that ROAR selects the individual with the best energy consumption, latency and bandwidth utilization as the ideal individual, thereby achieving a more balanced resource allocation among various performance indicators.

[0130] Figure 6 This embodiment compares the performance of the present invention with QELAR and RCAR in terms of average pack energy consumption. As can be seen from the figure, the average pack energy consumption of ROAR is consistently lower than that of QELAR and RCAR, indicating that ROAR has a significant advantage in energy efficiency.

[0131] Figure 7 In this embodiment, the performance of the present invention compared with QELAR and RCAR in terms of packet delivery rate is shown. The results show that the delivery rate of ROAR is significantly higher than that of the other two protocols, indicating that ROAR can more effectively guarantee the successful transmission of data.

[0132] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to the embodiments, those skilled in the art should understand 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 all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A routing method for an underwater acoustic communication network with dynamic optimization of communication resources, the underwater acoustic communication network comprising: The method includes a source node, a destination node, and multiple relay nodes, comprising: Step 1) The source node initiates the initialization of the underwater acoustic communication network, and each relay node constructs a local topology table by exchanging metadata packets; Step 2) The sending node determines the forwarding candidate set based on the location information of its neighboring nodes and its remaining energy; 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; specifically including: A multi-objective resource optimization model is constructed, which incorporates 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 thus expressed as a multi-objective optimization problem. The NSGA-II algorithm is used to solve the multi-objective optimization problem. Pareto optimal solution set is generated by non-dominated sorting and hybrid elite retention strategy. The best compromise solution is selected by combining the ideal point method to achieve communication resource optimization and obtain communication parameter configuration. Step 5) The sending node sends data packets to the optimal relay node according to the configured communication parameters; Step 6) Determine if the receiving node is the destination node: If it is the destination node, end; otherwise, 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, 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, characterized in that, Step 1) includes: Source node broadcast metadata: The metadata includes: packet type, node ID, timestamp, geographical location and remaining energy. Each relay node within the communication range receives the broadcast metadata and constructs a local topology table to maintain 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, characterized in that, Step 2) includes: The sending node determines the forwarding candidate set (candidateSet) based on the location information of its neighboring nodes and its remaining energy. candidateSet=Subset1∩Subset2 Where Subset1 is the set of neighboring 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 satisfy the energy constraint. The definitions of the two are as follows: Among them, Neighbor i It is the sending node n i The set of neighbors, l jd and l id Representing node n respectively j and node n i 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 4, characterized in that, Step 3) includes: The node with the highest forwarding priority in the candidate forwarding set is selected as the next-hop node, and the forwarding priority W is: Where β is the distance weight, D f Let α be the distance factor and α be the energy weight, satisfying the following equation: Where, p sent p represents the number of data packets already sent. total The number of all data packets to be sent.

6. The underwater acoustic communication network routing method for dynamic optimization of communication resources according to claim 1, characterized in that, The multi-objective optimization problem is: Given node indices i and j, the maximum allowable power of the underwater acoustic communication system is P. s,max Node n j The minimum power that can be correctly received is P s,min The bandwidth is B, and the maximum communication distance between nodes is d. max The bit error rate meets the threshold BER. th ; The goal is to minimize energy consumption, reduce end-to-end latency, and improve bandwidth utilization, which follows the formula: P s,min ≤P s,ij ≤P s,max Among them, v ij For node n i and node n j The relative speed of movement, where c is the speed of sound, f i0 The frequency of the first subcarrier. It is node n j The received bit error rate; Obtain the communication parameter configuration, including: selecting the optimal relay node number j from the candidate relay node set N of the current node. * Node n i to node n j Transmit power P s,ij Subcarrier spacing Δf ij Protection interval T g,ij Node n i To node n j Modulation method selected when transmitting data Where M{2,4,8,16,64} is the set of available modulation scheme candidates.

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