An AUV-Assisted Dynamic Hierarchical Routing Method for Underwater Acoustic Sensor Networks

Abstract

An AUV-assisted dynamic hierarchical routing method for underwater acoustic sensor networks, which relates to underwater communication. The routing of the underwater acoustic sensor network from the water surface to the bottom is divided into a top layer, a middle layer, and a bottom layer. Sensor nodes in different routing layers design different weight calculation methods according to the importance of information, the node energy loss situation, the characteristics of environmental noise, the belonging layer, and the node depth information, forming a node forwarding function F F . The AUV-assisted nodes transmit information to the surface sink nodes, and the sink nodes communicate wirelessly to transmit the data to the onshore control center. Each sink node processes the underwater information sensed by the nodes within its corresponding water area and the node's own energy and depth collected by the AUV, and broadcasts the updated hierarchical threshold to the underwater acoustic nodes. After receiving the hierarchical information, the nodes judge the layer they are in according to their actual working conditions, dynamically adjust the working mode, improve the underwater communication quality, reduce energy holes, and extend the network life.

Description

Technical Field

[0001] The present invention relates to underwater communication, and in particular to a dynamic hierarchical routing method for an AUV-assisted underwater acoustic sensor network. Background Art

[0002] With the continuous deepening of the exploration and research of the ocean field, it is urgent to develop an underwater acoustic sensor network to meet the application requirements in many fields such as underwater exploration, military surveillance, data collection, and underwater disaster prevention. How to improve the network performance of an underwater acoustic sensor network with low bandwidth, long delay, and low energy consumption supply is the main research direction at present. Designing an efficient and low-power underwater acoustic sensor network routing protocol to improve the efficient and reliable performance of data transmission between underwater acoustic nodes is a technical problem faced by the current development of underwater acoustic communication networking technology.

[0003] An autonomous underwater vehicle (AUV) equipped with underwater sensors has the advantage of strong mobility and has been widely used in underwater tasks such as ocean resource exploration and ocean environment adaptive sampling.

[0004] For an underwater acoustic sensor network, since GPS cannot be used normally underwater, it is difficult to locate underwater acoustic nodes. H. Yan et al. proposed a strategy for routing selection using node depth information (Yan H., et al. DBR: Depth-Based Routing for Underwater Sensor Networks[C] / / International Ifip-tc6 Networking Conference on Ad hoc&Sensor Networks. Springer-Verlag, 2008.). By obtaining the node depth value through the pressure sensor carried by the node, when forwarding data, only target nodes with a depth less than the current node are selected for forwarding, effectively avoiding the need to obtain global position information. Due to the special network environment of the underwater acoustic sensor network, the load levels of underwater sensor nodes vary, resulting in some nodes dying prematurely to form network energy holes, intermittent interruptions and additional delays in information transmission, further leading to the accelerated death of its surrounding nodes, seriously affecting the overall lifespan of the network. To provide a good solution and make the overall energy load of the network more balanced, researchers proposed a hierarchical routing algorithm for dense underwater acoustic sensor networks.

[0005] Among various hierarchical routing algorithms for underwater acoustic sensor networks, Gopi et al. (Gopi S, et al. E-PULRP: Energy Optimized Path Unaware Layered Routing Protocol for Underwater Sensor Networks[J]. IEEE Transactions on Wireless Communications, 2010.) proposed a hierarchical structure by combining the energy optimization principle. They layered around the sink node in the form of concentric shells surrounding the node and gave the calculation method of the horizontal layer radius. The network simulation results showed that this layering method could achieve a better packet delivery rate. Jafri M R et al. (Jafri M R, et al. iAMCTD: Improved Adaptive Mobility of Courier Nodes in Threshold-Optimized DBR Protocol for Underwater Wireless Sensor Networks[J]. International Journal of Distributed Sensor Networks, 2014.) simply layered in the vertical direction and then designed data forwarding functions for different layers in combination with the on-demand principle, taking into account the overall load balance of the network, reducing network energy consumption and propagation loss while taking into account the network throughput. Liu Yang et al. (Liu Yang, et al. Routing Algorithm for Underwater Sensor Networks in Rivers Based on Hierarchy[J]. Journal of Computer Applications, 2016.) combined the river environment, conducted a mechanical analysis of the tethered nodes, and proposed a routing strategy based on hierarchy, which was superior to the depth-based routing algorithm in terms of network redundancy and packet loss rate, and the network lifetime was also significantly improved.

[0006] To sum up, in the current research on the hierarchical problem of underwater acoustic sensor network routing, most are centered on nodes, layering in their propagation direction or simply fixing the layer in depth, and there is no relevant research on dynamically layering the routing in the depth direction by combining information such as the average remaining energy of network nodes and network density from the perspective of the global deployment of the overall network with the assistance of AUV. Summary of the Invention

[0007] The object of the present invention is to provide a dynamic hierarchical routing method for an AUV-assisted underwater acoustic sensor network that can balance the energy of the network load and extend the overall network lifetime. According to the different requirements of underwater acoustic communication quality and rate in different-depth ocean environments, a node data forwarding function is designed to select the transmission node path, improve the dynamic hierarchical routing mechanism, and apply it to solve the energy hole and "communication dead zone" problems easily generated in a dense underwater acoustic sensor network, so as to obtain a dynamic hierarchical routing method that takes into account network load balance and improves the overall network survival period.

[0008] The present invention includes the following steps:

[0009] 1) Assume that the underwater acoustic sensor nodes of the underwater acoustic sensor network are randomly distributed, denoted as node 1, node 2, node 3,.... The network is divided into three-layer structures, namely the top layer (L1), the middle layer (L2), and the bottom layer (L3) in sequence from the water surface to the bottom and from the lower level to the higher level: the initial distribution density and layer thickness of the nodes in the top layer (L1) and the bottom layer (L3) are both smaller than those in the middle layer (L2); multiple Sink nodes are distributed on the water surface, denoted as sink1, sink2, sink3,.... Radio communication links are established between the Sink nodes, and information can be transmitted to the shore-based control center; each Sink node maintains an information table of the network nodes in its own water area. Considering the node drift, the number of nodes in the sub-network within its corresponding water area is not fixed; each Sink node is equipped with multiple AUVs to work alternately, denoted as auv1, auv2, auv3,....

[0010] Among them, the Sink node has strong computing power and is responsible for processing the information forwarded by all nodes within its corresponding water area. It is powered by solar energy and the energy consumption problem is not considered; the AUV has strong mobility and swims periodically within the network. During this period, it broadcasts the arrival signal regularly, and its energy consumption problem needs to be considered; each Sink node is equipped with multiple AUVs to rotate. If the remaining energy of the current auv1 reaches the energy threshold, it will no longer receive new data. After reaching the water surface, it will transfer the data to the energy-sufficient auv2, which will take over the work, and the original auv1 will be charged.

[0011] 2) The Hello data packet only contains hierarchical boundary information. The Sink node broadcasts the Hello data packet underwater periodically to dynamically layer the network. Assume that the broadcast range of the Sink node can reach the lower boundary of the entire network, that is, each node in the network can receive the update of the hierarchical boundary information.

[0012] 3) After the underwater acoustic node receives the Hello data packet, it extracts the hierarchical boundary information in the packet to determine its own level and records its own level. It updates and maintains its own neighbor node information table according to the latest layering result; the data packet is always forwarded from the higher level to the lower level.

[0013] 4) All underwater acoustic nodes can be triggered by a sound source and become source nodes to originate data packets after being triggered. A non-Sink node that contains a data packet in its route is a sending node. Set a threshold for the data urgency level. The hard threshold is denoted by V th and the soft threshold is denoted by V ts . Then, the route request process of the sending node is divided into several cases according to the data urgency level: If the data urgency level is greater than the hard threshold V th , data transmission is immediately carried out; if the data urgency level is less than the soft threshold V ts , the data is discarded and not transmitted; if the data urgency level is between V th and the soft threshold V ts , the remaining energy of the sending node is further considered. If the remaining energy of the sending node is greater than the remaining energy threshold R t , transmission is carried out; if it is less than R t , wait to consider transmission during the next round of forwarding. The urgency level of this data packet is correspondingly reduced, and repeat the current step 4);

[0014] 5) If the sending node in step 4) confirms the need to forward a data packet, the sending node will select the best next-hop forwarding node from the neighbor node information table as the receiving node for data forwarding; when an AUV passes by within the transmission range of the sending node, the AUV receives the broadcast information from the sending node, acts as a relay node, receives the data packet broadcast by the receiving node for cooperative communication, and forwards it to the receiving node;

[0015] Among them, the AUV broadcasts the arrival signal regularly during movement. When a node receives the arrival signal, it will return its own serial number, depth, and remaining energy information to the AUV; if there are no neighbor nodes that can be transmitted within the communication range of the node at this time, the AUV will be regarded as a new neighbor node, add its information to its own neighbor node information table, and forward the data packet to the next hop through the AUV to solve the "communication dead zone" problem; if the node does not receive the AUV arrival signal when the AUV leaves, the information of the AUV will be deleted from its own neighbor node information table;

[0016] 6) The receiving node is updated to a new sending node;

[0017] 7) The sending node judges whether the next hop can reach the Sink node according to whether the Sink node is included in its communication range. If it has not reached, repeat steps 5) and 6) until it is successfully transmitted to the Sink node; when the AUV forwards a data packet and the Sink node is included in its communication range, it will directly forward the data packet to the Sink node;

[0018] 8) Considering that in different routing hierarchical structures, the environmental conditions, energy consumption, belonging levels, and optimization objectives of nodes are different, the signal-to-noise ratio, remaining energy, and depth parameters for calculating the weights of their neighbor nodes will change. A forwarding function is designed to select the best receiving node. The forwarding weights of all neighbor nodes within the transmission range of a node are respectively represented as W1, W2, W3, …. Then, the node to be forwarded will select the neighbor node with the largest weight value as the receiving node for forwarding. The forwarding function is expressed as: F F = W max ; If the Sink node is included within the transmission range, then F F = W sink ;

[0019] In step 8), according to the different characteristics of the environmental conditions of the water layers where the nodes are located, their own energy consumption situations, and forwarding optimization objectives, the signal-to-noise ratio, remaining energy, and depth parameters for calculating the weights change. Then, the forwarding function F F has different expressions in different layers of the three-layer routing structure. The specific expression formula is:

[0020] (1) Top layer: The nodes within the layer have a shallow depth and are close to the water surface. They are significantly affected by interface interference, ship activities, and noise. To ensure signal quality, the forwarding function should pursue the minimum propagation loss to achieve the best signal-to-noise ratio. The nodes within the layer are close to the Sink node and are prone to energy holes. Considering the remaining energy information of the nodes, the formation of energy holes is reduced, and the network lifetime is extended. Its forwarding function F F is:

[0021]

[0022]

[0023] In the formula, w1 is a weight constant, which can be adjusted according to the specific scenario; E res is the remaining energy of the node; dr i is the Euclidean distance between the sending and receiving nodes; L is the level to which the node belongs; LSNR is the signal-to-noise ratio without positioning; P t is the constant transmission power; dl is the depth difference between the sending and receiving nodes; f is the signal frequency (kHz); A is the path attenuation loss, and its product with the environmental noise N constitutes the environmental attenuation coefficient.

[0024] (2) Middle layer: The data forwarding of the nodes within the layer is the most frequent, and the number of nodes is large. If an energy hole appears, it will cause a large-scale and rapid death of the surrounding nodes. Therefore, it is necessary to consider the influence of both transmission energy consumption and transmission efficiency to reduce the influence of energy holes and maximize the realization of network energy balance to effectively improve the network lifetime. Its forwarding function F F is:

[0025]

[0026] Wherein, w2 is a weight constant, which can be adjusted according to the specific scenario; E res is the remaining energy of the node; dl is the depth difference between the sending and receiving nodes; L is the layer to which the node belongs.

[0027] (3) Bottom layer: The in-layer channel loss is not large, the node forwarding load is large, there are many marine organisms, the underwater interference has a great impact, and it is also affected by the mineral distribution. It pursues long-distance (mainly in the vertical direction) transmission to reduce the impact of flooding. Its forwarding function F F is:

[0028]

[0029] Wherein, w3 is a weight constant, which can be adjusted according to the specific scenario; E res is the remaining energy of the node; LSNR is the non-positioning signal-to-noise ratio; dl is the depth difference between the sending and receiving nodes; l is the node depth; L is the layer to which the node belongs.

[0030] 9) Each time the AUV swims back to the communication range of the Sink node, it aggregates and transmits the information of each node in the network collected to the Sink node, and the Sink node performs the update calculation and broadcast of the hierarchical boundary.

[0031] In step 9), the hierarchical depth boundary between the top layer (L1) and the middle layer (L2) of the network routing is represented as D1, and the hierarchical depth boundary between the middle layer (L2) and the bottom layer (L3) is represented as D2. With the continuous increase of the overall network energy consumption and the change of network density, the values of D1 and D2 will be dynamically adjusted. Each node determines the layer it belongs to according to its own depth to achieve the dynamic update of the hierarchical structure; with the continuous increase of the overall network energy consumption and the dynamic change of network density, the values of D1 and D2 will be dynamically changed and adjusted according to the overall network status. The specific update formula is expressed as:

[0032] D 1* = wd1 * D1 * Nd * R ave

[0033]

[0034] Wherein, D 1* and D 2* respectively represent the updated hierarchical depth boundary between the top layer (L1) and the middle layer (L2), and the updated hierarchical depth boundary between the middle layer (L2) and the bottom layer (L3); wd1 and wd2 are weight constants, which can be adjusted according to the specific scenario; Nd is the network density; R ave is the average remaining energy of the node.

[0035] The present invention can effectively balance the loads of network nodes in underwater acoustic data transmission, thereby reducing the occurrence of network energy holes and extending the overall network life and survival cycle. Considering the problems of unbalanced node loads and possible "communication dead zones" in the data transmission process of dense underwater acoustic sensor networks, the present invention intends to combine the characteristics of the underwater acoustic environment and a data forwarding mode based on the hierarchical idea, and through AUV-assisted communication, perform dynamic routing selection for underwater acoustic multi-hop networks, aiming to obtain a routing selection method that can balance the network load energy and extend the overall network life.

[0036] The present invention has the following outstanding advantages:

[0037] 1) In underwater acoustic communication, the physical layer loss and the total energy consumption of the entire network are related to the distance, and the distance and energy are in an exponential relationship. Short-distance transmission can effectively save energy, but only using the distance as the standard for selecting transmission may cause the problem of "communication dead zones"; adopting a dynamic network hierarchical routing strategy, data is transmitted layer by layer and hop by hop according to the hierarchy, avoiding repeated transmission of nodes in the same layer, and designing an AUV to assist communication can effectively solve the problem of "communication dead zones" and improve the network connectivity, reliability, and fault tolerance;

[0038] 2) Design a dynamic network hierarchical mechanism, consider the situation of node death and nodes deviating from the original hierarchy due to factors such as water flow, and dynamically update the modulation routing hierarchy from the perspective of the overall network global deployment, improve the flexibility of the mechanism, ensure the network performance when the network density decreases, and at the same time extend the network survival cycle;

[0039] 3) Considering the working characteristics of nodes at different levels, design forwarding functions for nodes at different levels, utilize the high flexibility and high mobility of AUVs to alleviate the formation of network energy holes, balance the network load, and improve the network life. Description of the Drawings

[0040] Figure 1 It is a scenario diagram of the dynamic hierarchical routing data transmission of an AUV-assisted underwater acoustic sensor network of the present invention.

[0041] Figure 2 It is a flowchart of the dynamic hierarchical routing method of an AUV-assisted underwater acoustic sensor network of the present invention.

[0042] Figure 3 It is a flowchart of the node routing request of the dynamic hierarchical routing method of an AUV-assisted underwater acoustic sensor network of the present invention.

[0043] Figure 4 It is a flowchart of the node data packet forwarding based on the hierarchy of the dynamic hierarchical routing method of an AUV-assisted underwater acoustic sensor network of the present invention.

[0044] Figure 5This is a comparison chart of the dynamic hierarchical results of different network life stages of the AUV-assisted dynamic hierarchical routing method for an underwater acoustic sensor network in the present invention.

[0045] Figure 6 This is a comparison chart of the node death situations between the static hierarchical routing method and the AUV-assisted dynamic hierarchical routing method for an underwater acoustic sensor network in the present invention. Specific embodiments

[0046] The following describes the present invention in detail with reference to the accompanying drawings and specific embodiments.

[0047] As Figure 1 shown, the embodiments of the present invention include the following steps:

[0048] 1) Suppose there are n randomly distributed underwater acoustic sensor nodes in the underwater acoustic sensor network, denoted as node 1, node 2, node 3, …, node i, … node n. The network is divided into three-layer structures of the top layer, the middle layer, and the bottom layer from the water surface to the bottom and from the lower level to the higher level, and their levels are respectively represented as L = 1, L = 2, and L = 3: The initial distribution density and layer thickness of the nodes in the top layer and the bottom layer are both less than those in the middle layer. There are m Sink nodes distributed on the water surface, denoted as sink1, sink2, sink3, …, sinkm. The Sink nodes can transmit information to the shore-based control center through radio communication; each Sink node maintains an information table of the network nodes in its own water area. Considering the node drift, the number of nodes in the sub-network within its corresponding water area is not fixed; each Sink node is equipped with multiple AUVs to work in turn, denoted as auv1, auv2, auv3, …; As Figure 1 shown in, there are 11 randomly distributed nodes underwater, denoted as node 1, node 2, node 3, …, node 11 respectively. The underwater data they collect will all be forwarded to the water surface aggregation node, denoted as sink1 in the figure. Sink1 is equipped with 2 AUVs to work in turn, denoted as auv1 and auv2 respectively;

[0049] Among them, sink1 has strong computing power and is responsible for processing the information forwarded by node 1, node 2, node 3, …, node 11. It is powered by solar energy and the energy consumption problem is not considered;

[0050] 2) The Hello data packet only contains hierarchical boundary information: the hierarchical boundary D1 between the top layer and the middle layer, and the hierarchical boundary D2 between the middle layer and the bottom layer. Sink1 periodically broadcasts the Hello data packet downward to perform dynamic hierarchical division of the network. The broadcast range can reach the lower boundary of the entire network, that is, node 1, node 2, node 3, …, node 11 can all receive the updates of D1 and D2;

[0051] 3) auv1 and auv2 have strong mobility and take turns to perform periodic swimming in the network. During the swimming period, they regularly broadcast arrival signals, as Figure 2As shown in the figure, when the AUV receives the request forwarding signal broadcast by the node during movement, the auxiliary node forwards the data packet to the next best neighbor node or sink1 to assist in communication; at the same time, it collects the node number, depth, and remaining energy information returned by the node.

[0052] 4) When the AUV dives, its depth continuously increases until it reaches the lower boundary of the network, and then it starts to turn around and move upward; when moving upward, it will repeat the cooperative communication process and the process of collecting node information in step 3) until it reaches within the communication range of sink1, and then transmits the data packet carried to sink1. It detects the remaining energy of auv1 itself. If it reaches the energy threshold, it will be replaced by auv2 for work, and the original auv1 will be charged.

[0053] 5) After sink1 receives the information of node 1, node 2, node 3,..., node 11 collected by the AUV, it calculates the update of D1 and D2, and directly broadcasts them downward to each node in the form of Hello data packets. The specific calculation formula is:

[0054] D 1* =wd1*D1*Nd*R ave

[0055]

[0056] In the formula, D 1* and D 2* respectively represent the updated top-layer and middle-layer hierarchical depth boundaries and the updated middle-layer and bottom-layer hierarchical depth boundaries; wd1 and wd2 are weight constants that can be adjusted according to the specific scenario; Nd is the network density; R ave is the average remaining energy of the node. It can be seen that due to the update and transformation of node information, D1 and D2 will also change dynamically, that is, the underwater routing hierarchy changes dynamically.

[0057] 6) After node 1, node 2, node 3,..., node 11 receive the Hello data packet, they extract the hierarchical depth boundaries D1 and D2 in the packet for their own level determination, record their own levels, and update and maintain their own neighbor node information tables according to the latest hierarchical results.

[0058] 7) Each node may be triggered by a sound source. As Figure 1 shown, after node 11 is triggered, it becomes the source node, and its routing request process is as Figure 3 shown. Set the threshold of the data urgency: the hard threshold is represented by V th , indicating that the data is very urgent and needs to be transmitted immediately; the soft threshold is represented by V ts , indicating that the data is not important and does not need to be transmitted. If the data urgency is greater than the hard threshold V th , then the data will be transmitted immediately; if the data urgency is less than the soft threshold V ts, the data is discarded and not transmitted; if the data urgency level is between V th and the soft threshold V ts , the remaining energy of node 11 is further considered. If the remaining energy of node 11 is greater than the remaining energy threshold R t , it is transmitted; if it is less than R t , it waits to be considered for transmission during the next round of forwarding. At the same time, the urgency level of the current data packet decreases accordingly, and the current steps are repeated until the data packet is discarded or the transmission is confirmed;

[0059] 8) If node 11 confirms the need to forward a data packet in step 7), node 11 enters the data forwarding phase. As shown in Figure 4 , node 11 selects the best next-hop forwarding node from the neighbor node information table according to the forwarding function for data forwarding; Figure 1 , as shown in, when there are no neighbor nodes within the transmission range of node 11 and auv1 passes by, auv1 will be used as a new neighbor node, and its information will be added to its own neighbor node information table. auv1 will act as a relay node, receive the data packet broadcast by node 11 for cooperative communication, and forward it to the next-hop node 8 to solve the "communication dead zone" problem; when auv1 leaves and the node does not receive the arrival signal, its information will be deleted from its own neighbor node information table;

[0060] 9) When node 8 forwards data, although both node 55 and node 6 are its neighbor nodes, according to the forwarding function, it is calculated that node 6 is the best neighbor node, and the data packet is delivered to it; steps 8) and 9) are repeated until the data packet is successfully transmitted to sink1;

[0061] Considering that in different routing hierarchical structures, the environmental conditions, energy consumption, hierarchical belonging, and optimization objectives of nodes are different, and the signal-to-noise ratio, remaining energy, and depth parameters for calculating the weights of neighbor nodes change, a forwarding function is designed to select the best receiving node; the forwarding weights of k neighbor nodes within the transmission range of the node are respectively expressed as W1, W2, W3,..., W k , then the node to be forwarded will select the node with the largest weight value among the neighbor nodes for forwarding, that is, the forwarding function F F =W max ; if the Sink node is included within the transmission range, then F F =W sink ; F F The specific expression formula is:

[0062] (1) Top layer: The nodes within this layer have a shallow depth inside the layer, are close to the water surface, and are significantly affected by interface interference, ship activities, and noise. To ensure signal quality, the forwarding function should aim for the minimum propagation loss to achieve the best signal-to-noise ratio. The nodes within the layer are close to the Sink node, and energy holes are likely to occur. Considering the remaining energy information of the nodes, the formation of energy holes is reduced, and the network lifetime is extended.

[0063]

[0064]

[0065] In the formula, w1 is a weight constant, which can be adjusted according to the specific scenario; E res is the remaining energy of the node; dr i is the Euclidean distance between the transceiver nodes; L is the layer to which the node belongs; LSNR is the signal-to-noise ratio without localization; P t is the constant transmission power; dl is the depth difference between the transceiver nodes; f is the signal frequency; A is the path attenuation loss, and the product of it and the environmental noise N constitutes the environmental attenuation coefficient.

[0066] (2) Middle layer: The data forwarding of the nodes within this layer is the most frequent, and the number of nodes is large. If energy holes occur, it will cause the large-scale and rapid death of the surrounding nodes. Therefore, considering the influence of both transmission energy consumption and transmission efficiency, the influence of energy holes is reduced, and the network energy balance is maximally achieved to effectively improve the network lifetime.

[0067]

[0068] In the formula, w2 is a weight constant, which can be adjusted according to the specific scenario; E res is the remaining energy of the node; dl is the depth difference between the transceiver nodes; L is the layer to which the node belongs.

[0069] (3) Bottom layer: The channel loss within this layer is not large, the forwarding load of the nodes is large, there are many marine organisms, the underwater interference is significant, and it is also affected by the mineral distribution. It aims for long-distance (mainly in the vertical direction) transmission to reduce the influence of flooding.

[0070]

[0071] In the formula, w3 is a weight constant, which can be adjusted according to the specific scenario; E res is the remaining energy of the node; LSNR is the signal-to-noise ratio without localization; dl is the depth difference between the transceiver nodes; l is the depth of the node; L is the layer to which the node belongs.

[0072] Next, the feasibility of the method described in the present invention is verified by computer simulation.

[0073] To simulate the underwater acoustic sensor network, as Figure 5As shown in (a), a network topology model of underwater acoustic sensor nodes is randomly arranged. There are a total of 64 nodes, denoted as node 1, node 2, node 3, …, node 64; 4 Sink nodes, denoted as sink1, sink2, sink3, sink4; initially, there are 16 top-layer nodes, 32 middle-layer nodes, and 16 bottom-layer nodes.

[0074] It is assumed that the maximum depth of the underwater acoustic sensor network is 1 km, and the maximum horizontal range is 1 km. For successful data transmission, the distance between two nodes needs to be less than 200 m. The transmission result is determined when the data packet is transmitted to the Sink node; otherwise, the transmission is judged to be a failure. The power consumption of the node in the sending, receiving, and idle modes is 2 W, 0.1 W, and 10 mW respectively. The node is initially equipped with 70 J, the initial value of D1 is 300 m, and the initial value of D2 is 700 m.

[0075] The algorithm steps are as follows:

[0076] (1) Randomly select node i as the initial data sending node.

[0077] (2) According to the depth information of the sending node, determine whether its next hop can reach the Sink node. If it can, directly forward the data packet to the nearest Sink node to successfully complete the data transmission; if the next hop cannot directly reach the Sink node, classify all the normally working live nodes within its communication range as the neighbor nodes of the sending node. Calculate the weights of the neighbor nodes according to the forwarding function, and select the node j with the largest weight as the receiving node for data forwarding; if the number of neighbor nodes is 0, determine whether there is an AUV for auxiliary communication according to the running time. If there is, the data can be successfully transmitted to the next hop; if not, wait. The maximum waiting time is 300 s, and if the maximum waiting time is exceeded, the transmission fails.

[0078] In step (2), the specific formula of the forwarding function is as follows:

[0079]

[0080] (3) Update the receiving node as the new sending node and repeat step (2).

[0081] (4) Whether the data packet is successfully transmitted to the Sink node or the transmission fails, it is regarded as the end of the transmission, which is 1 round of transmission. After every 20 rounds of transmission, update the values of the hierarchical boundaries D1 and D2. All nodes judge their own levels according to their own depths: if the depth is less than or equal to D1, it is the top layer; if the depth is greater than D1 and less than or equal to D2, it is the middle layer; if the depth is greater than D2, it is the bottom layer.

[0082] In step (4), the specific update formulas of D1 and D2 are as follows:

[0083] D1* = wd1 * D1 * Nd * R ave

[0084]

[0085] (5) When the node is a sending node, the sending power is 2W; when the node is a receiving node, the receiving power is 0.1W; when idle, the working power of the node is 10mW. If the remaining energy of the node is less than the energy threshold, it is determined that the node is in a dead state, unable to communicate, and exits the network.

[0086] (6) Update the number of remaining live nodes in the network, update the network density and the average remaining energy of the network. The specific calculation formulas are as follows:

[0087]

[0088]

[0089] In the formula, N alive , represents the number of live nodes in the network, N dead represents the number of dead nodes in the network, e n represents the remaining energy of node n.

[0090] (7) When the network density is less than or equal to 20%, it is determined that the network is dead, that is, the network survival period is defined as the time when the network density drops from 100% to 20%.

[0091] For a better display of the effect of the dynamic hierarchical forwarding method, the method described in the invention is verified by computer simulation as follows:

[0092] As Figure 5 (b) shows, after 80 rounds of transmission, that is, after 4 updates of the hierarchical boundary, the network hierarchical result is significantly different from the initial network hierarchy. The distances between the top layer and the bottom layer have both decreased, and the distance between the middle layers has increased; as Figure 5 (c) shows, after 400 rounds of transmission, 24 dead nodes have appeared in the network, and the remaining live nodes are mainly middle nodes.

[0093] To verify the advantages of the dynamic hierarchical routing method described in the invention compared with the static hierarchical routing method in terms of extending the network life and alleviating the node death situation, the node survival conditions of the dynamic hierarchical routing method and the static hierarchical routing method are simulated by computer as follows:

[0094] The comparison chart of the node death situation between the static hierarchical routing method and the AUV-assisted underwater acoustic sensor network dynamic hierarchical routing method of the present invention is as Figure 6 shown. From Figure 6 it can be seen that the node death speed of the dynamic hierarchical routing method is slower and the overall network life is longer.

[0095] The present invention provides a dynamic hierarchical forwarding scheme in underwater acoustic sensor network routing by combining the on-demand principle and the hierarchical routing algorithm. Adopting the hierarchical idea, data is transmitted hop by hop layer by layer according to the hierarchy, solving the "communication dead zone" problem and improving network connectivity, reliability and fault tolerance. In underwater acoustic communication, the physical layer loss and the total energy consumption of the whole network are related to the distance, and the distance and energy are in an exponential relationship. Considering the distance between nodes, short-distance transmission can effectively save energy. The remaining energy of the nodes is used as a measure for electing candidate nodes, balancing the network energy consumption and prolonging the network lifetime. Considering that nodes may deviate from the original hierarchy due to water flow, etc., the network has good flexibility. The Sink node only needs to broadcast D1 and D2, reducing data redundancy. There is no need for clustering, and there is no additional overhead of clusters generated by cluster heads and super nodes. The present invention uses the dynamic hierarchical routing algorithm to solve the problems of unbalanced network energy load and "communication dead zone", reducing the energy consumption of the underwater acoustic cooperative communication network, improving the communication efficiency and prolonging the network survival period.

Claims

1. An AUV-assisted dynamic hierarchical routing method for an underwater acoustic sensor network, characterized in that: Considering that in different routing hierarchical structures, the environmental conditions, energy consumption, belonging levels and optimization objectives of nodes are different, the signal-to-noise ratio, remaining energy and depth parameters for calculating the weights of neighbor nodes will change. A forwarding function is designed to select the best receiving node; the forwarding weights of all neighbor nodes within the transmission range of a node are respectively expressed as W1, W2, W3,.... Then the node to be forwarded will select the neighbor node with the largest weight value as the receiving node for forwarding, and the forwarding function is expressed as: F F = W max ; If the transmission range includes the Sink node, then F F = W sink ; Among them, the forwarding function F F is expressed differently in different layers of the three-layer routing structure, and the specific expression formula is: (1) Top layer: Nodes within the layer are close to the Sink node, making it easy to form energy holes. Considering the remaining energy information of nodes, reducing the formation of energy holes and extending the network lifetime, the forwarding function F F is expressed as: where w1 is a weight constant, which is adjusted according to the specific scenario; E res is the remaining energy of the node; dr i is the Euclidean distance between the transceiver nodes; L is the level to which the node belongs; LSNR is the non-positioning signal-to-noise ratio; P t is the constant transmission power; dl is the depth difference between the transceiver nodes; f is the signal frequency; A is the path attenuation loss, and the product of it and the environmental noise N constitutes the environmental attenuation coefficient; (2) Intermediate layer: Considering the influence of both transmission energy consumption and transmission efficiency to reduce the impact of energy holes and achieve network energy balance, thereby effectively improving the network lifetime, the forwarding function F F is expressed as: where w2 is a weight constant, which is adjusted according to specific scenarios; E res is the remaining energy of the node; dl is the depth difference between the sending and receiving nodes; L is the level to which the node belongs; (3) Bottom layer: The in-layer channel loss is not significant, the node forwarding load is large, there are many marine organisms, the underwater interference has a great impact, and it is also affected by the mineral distribution. To pursue long-distance and vertical transmission to reduce the impact of flooding, the forwarding function F F is expressed as: where w3 is a weight constant, which is adjusted according to the specific scenario; E res is the remaining energy of the node; LSNR is the positioning-free signal-to-noise ratio; dl is the depth difference between the transceiver nodes; l is the depth of the node; L is the level to which the node belongs.

2. The AUV-assisted dynamic hierarchical routing method for an underwater acoustic sensor network according to claim 1, the method further includes: Assume that the underwater acoustic sensor nodes in the underwater acoustic sensor network are randomly distributed, expressed as node 1, node 2, node 3,.... The network is divided into three hierarchical structures: the top layer, the middle layer and the bottom layer from the water surface to the bottom and from the lower level to the higher level in sequence. The initial distribution density and layer thickness of the nodes in the top layer and the bottom layer are both smaller than those in the middle layer; multiple Sink nodes are distributed on the water surface, expressed as sink1, sink2, sink3,.... The Sink nodes transmit information to the shore-based control center through radio communication; each Sink node maintains an information table of the network nodes in its own water area. Considering the node drift, the number of nodes in the sub-network within its corresponding water area range is not fixed; each Sink node is equipped with multiple AUVs to work alternately, expressed as auv1, auv2, auv3,....

3. The AUV-assisted dynamic hierarchical routing method for an underwater acoustic sensor network according to claim 1, the method further includes: The Hello packet only contains hierarchical boundary information. The Sink node periodically broadcasts the Hello packet underwater to dynamically layer the network. Assume that the broadcast range of the Sink node can reach the lower boundary of the entire network, that is, each node in the network can receive the update of the hierarchical boundary information.

4. The AUV-assisted dynamic hierarchical routing method for an underwater acoustic sensor network according to claim 1, the method further includes: After receiving the Hello packet, the underwater acoustic node extracts the hierarchical boundary information in the packet to determine its own level and records its own level, and updates and maintains its own neighbor node information table according to the latest layering result; The data packet is always forwarded from the higher level to the lower level.

5. The AUV-assisted dynamic hierarchical routing method for an underwater acoustic sensor network according to claim 1, the method further includes: All underwater acoustic nodes are triggered by the sound source and become source nodes to originate data packets after being triggered; non-Sink nodes that contain data packets in the routing are sending nodes; set the threshold of data urgency, the hard threshold is represented by V th and the soft threshold is represented by V ts Then, the routing request process of the sending node is divided into three cases according to the urgency of the data: If the data urgency is greater than the hard threshold V th , data transmission is immediately carried out; if the data urgency is less than the soft threshold V ts , the data is discarded and not transmitted; If the data urgency level is at V th and the soft threshold V ts , then consider the remaining energy of the sending node; if the remaining energy of the sending node is greater than the remaining energy threshold R t , then perform transmission; if it is less than R t , then wait until the next round of forwarding to consider transmission, and the urgency level of this data packet is correspondingly reduced, and repeat the current method.

6. The AUV-assisted dynamic hierarchical routing method for an underwater acoustic sensor network according to claim 1, the method further includes: Every time the AUV swims back into the communication range of the Sink node, it summarizes and transmits the information of each network node collected to the Sink node, and the Sink node performs the update calculation and broadcast of the hierarchical boundary; Among them, the depth boundary between the top layer and the middle layer of the network routing is denoted as D1, and the depth boundary between the middle layer and the bottom layer is denoted as D2. With the continuous increase of the overall network energy consumption and the change of network density, the values of D1 and D2 will be dynamically adjusted, and each node determines its own layer according to its own depth to achieve dynamic update of the hierarchical structure; With the continuous increase of the overall network energy consumption and the dynamic change of network density, the values of D1 and D2 will be dynamically adjusted according to the overall network status, and the specific update formula is expressed as: D 1* = wd1 * D1 * Nd * R ave Where D 1* and D 2* respectively represent the updated depth boundaries of the top layer and the middle layer and the updated depth boundaries of the middle layer and the bottom layer; wd1 and wd2 are weight constants, which are adjusted according to specific scenarios; Nd is the network density; R ave is the average remaining energy of nodes.

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