Underwater acoustic sensor network routing method based on fuzzy logic decision

Abstract

The invention relates to an underwater acoustic sensor network routing method based on fuzzy logic, which comprises the following steps that: a Sink node periodically broadcasts a HELLO packet to perceive topological change, and each node locally and dynamically maintains a parameter Hcur representing the hop count of the node for representing the hop count from the node to the Sink node; in the relay selection process, the sending node broadcasts a PING packet; after the neighbor node monitors the PING packet, the neighbor node whose hop count to the Sink node is less than or equal to that of the sending node becomes a candidate node, and the candidate node calculates the link quality between the sending node and the node and replies the PONG packet in a point-to-point manner; (4) within the waiting time, the sending node receives the PONG packet replied from the candidate node, and constructs a candidate node routing table; and (5) after the timing of the waiting time is finished, selecting an optimal forwarding node based on a candidate node routing table and a fuzzy system.

Description

Technical Field

[0001] The invention belongs to the technical field of underwater acoustic communication network routing layer, and relates to an underwater acoustic sensor network routing method algorithm based on fuzzy logic decision. Background Art

[0002] Underwater routing methods are one of the keys to ensure efficient multi-hop transmission of data in underwater acoustic sensor networks (UASNs). Although network-layer routing methods are emerging in wireless networks, due to the complexity and variability of underwater environments and network characteristics, as well as limited energy, it is difficult to directly transplant related routing methods in wireless communications into underwater networks. Therefore, it is very challenging to design a high-performance routing method for underwater acoustic sensor networks.

[0003] The rapid changes in acoustic channels in underwater environments may lead to time-varying and asymmetric link quality. In addition, overuse of certain nodes can cause premature node failure, shortening the life of the network. In addition to link quality issues, UASNs face other challenges. Due to the high cost of underwater nodes, they are usually sparsely deployed, which may lead to an insufficient number of nodes covering the target area, resulting in void areas, thereby reducing the packet delivery rate. The irregular movement of nodes causes the network topology to change continuously, which may cause the routing path to fail due to link disconnection, further reducing the reliability of data transmission. In addition, the difficulty in obtaining geographic location information of underwater nodes increases the complexity of network management and routing selection. Summary of the invention

[0004] In view of the above problems, the present invention proposes an underwater acoustic sensor network routing method based on fuzzy logic decision-making, which can be applied to the underwater acoustic sensor network scenario. The present invention uses a fuzzy control system (FCS) to select the best forwarding node (BFN). The relative residual energy, link quality and number of hops from the relative distance Sink node of the candidate node are comprehensively considered as input parameters of the fuzzy system. Fuzzy control can handle the interaction of uncertainties of different parameters in the process of data packet forwarding. The application of fuzzy control in routing protocols has significant advantages, such as improving network reliability, extending network life, handling uncertainty and simplifying calculations. The technical solution of the present invention is as follows:

[0005] A fuzzy logic based underwater acoustic sensor network routing method, the data packets used include HELLO packets, PING packets and PONG packets, wherein:

[0006] The PING packet contains: the sending node ID, the next hop node ID and the number of hops from the Sink node;

[0007] The PONG packet contains: the sending node ID, the next hop node ID, the remaining energy of the candidate node, the link quality and the number of hops from the sink node;

[0008] The underwater acoustic sensor network routing method comprises the following steps:

[0009] (1) Sink nodes periodically broadcast HELLO packets to sense topology changes. Each node dynamically maintains a parameter Hcur representing the hop count of the node locally, which is used to represent the hop count from the node to the sink node. All nodes in the entire network are time synchronized. If a node hears a HELLO packet within the HELLO broadcast time, it extracts the sending node ID and the hop count Hcount from the sink node. If the Hcount in the packet is less than the Hcur-1 of this node, the hop count of the node is updated to Hcount+1, the Hcount in the HELLO packet is updated to Hcount+1, and the HELLO packet is forwarded. Otherwise, the HELLO packet is directly discarded.

[0010] (2) During the relay selection process, the sending node broadcasts a PING packet;

[0011] (3) After the neighbor node listens to the PING packet, the neighbor node whose hop count from the Sink node is less than or equal to the sending node becomes the candidate node. The candidate node calculates the link quality between the sending node and the node, and replies with a PONG packet point-to-point;

[0012] (4) During the waiting time, the sending node receives the PONG packet replied from the candidate node and builds the candidate node routing table;

[0013] (5) after the waiting time ends, selecting the best forwarding node based on the candidate node routing table and the fuzzy system;

[0014] (6) The sending node sets the next hop node ID in the data packet as the output optimal forwarding node ID of the fuzzy system, and then forwards the data packet. The data packet structure contains three parts: header, routing information and data payload; among which, the routing information includes the next hop node ID, forwarding times and routing void_flag.

[0015] Furthermore, the routing hole problem can be solved in the following ways:

[0016] Use HELLO broadcast to mark the void node: the void_flag of all nodes is initialized to 0; during the most recent HELLO packet broadcast, if the node does not receive the HELLO packet, it considers itself a void node and sets the void_flag to 1; during the forwarding of data packets, when the neighbor node listens to the PING packet, it first checks the void_flag of the node; if the void_flag is 0, the PONG packet can be sent; if the void_flag is 1, the PONG packet cannot be sent;

[0017] Use information interaction between nodes to mark void nodes: When the source node or the current node has data to send, it broadcasts a PING packet; if it does not receive a PONG packet from a neighboring node within the waiting time, it considers itself a void node, sets void_flag to 1, and re-forwards the data packet to the previous hop node; after receiving the data packet, the previous hop node identifies and extracts void_flag; if void_flag is 1, the second priority candidate node is selected to re-forward the data packet.

[0018] Furthermore, a packet delivery probability model is used to measure the link quality between nodes. The method is as follows: The underwater packet delivery probability p is modeled as a function of the transmission distance d, the number of bits m, and the signal frequency f, and is expressed as: p(d,m,f)=(1-p b (d,f)) m ; Among them, p b (d,f) is the bit error rate; f SNR (d, f, X) represents the probability density at a given transmission distance d, signal frequency f, and average signal-to-noise ratio X. By considering the path loss gain and loss, the average signal-to-noise ratio SNR at the receiving end is modeled as: Among them, E b represents the energy per bit transmitted, A(d,f) represents the path loss of the transmission distance d and the signal frequency f, and N0 represents the noise power density under the additive white Gaussian noise (AWGN) channel; the path loss of the acoustic link is expressed as: A(d,f) = d k α(f) d ; where k∈[1,2] represents the propagation loss factor related to the propagation geometry, and α(f) represents the absorption coefficient.

[0019] Furthermore, the fuzzy system includes three steps: variable fuzzification, fuzzy reasoning according to fuzzy rules, and defuzzification; in variable fuzzification, the residual energy, link quality and relative hop count of the candidate node are fuzzified according to the input membership function.

[0020] The invention proposes a fuzzy logic-based underwater acoustic sensor network routing method, in which the sending node obtains information such as real-time link quality, remaining energy, and the number of hops from the sink node by exchanging information with neighboring nodes, and uses a fuzzy control system (FCS) to select the best next hop node (BFN). When the source node or the current node has data to send, a PING packet is broadcast first, and the neighboring node will reply with a PONG packet containing node information after receiving it. After receiving this information, the sending node selects the best next hop node based on this information. In addition, the method also effectively solves the routing hole problem by introducing the void_flag flag bit. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 It is the format of routing table, HELLO packet, PING packet and PONG packet.

[0022] Figure 2 Is the data packet structure

[0023] Figure 3 This is a flow chart of the underwater acoustic sensor network routing method based on fuzzy logic decision making.

[0024] Figure 4 This is a flow chart of the routing hole recovery mechanism.

[0025] Figure 5 It is a fuzzy system

[0026] Figure 6 is the membership function, (a) is the membership function diagram of relative residual energy, (b) is the membership function diagram of link quality, (c) is the membership function diagram of relative Sink node hop count, and (d) is the membership function diagram of output priority

[0027] Figure 7 Relay selection process diagram DETAILED DESCRIPTION

[0028] The present invention will be described below in conjunction with the accompanying drawings.

[0029] The present invention provides a method for routing underwater acoustic sensor networks based on fuzzy logic decision making. The core idea of ​​the method is that the sending node can exchange information with neighboring nodes to obtain information such as real-time link quality, remaining energy, and the number of hops from the sink node. When the source node or the current node has data to send, it first broadcasts an echo request (PING) packet, and the packet structure is as follows: Figure 1 After the neighbor node listens to the PING packet, the neighbor node whose hop count from the Sink node is less than or equal to the sending node becomes a candidate node. It will first calculate the link quality between the sending node and then reply with a point-to-point echo response (PONG) packet. The packet structure is as follows: Figure 1 As shown in Figure 1, the PONG packet contains information such as the remaining energy of the candidate node, link quality, and the number of hops from the Sink node. The sending node receives the PONG packet during the waiting time and establishes a candidate node routing table. The routing table structure is as follows: Figure 1 As shown in the figure. After the waiting time is over, the fuzzy control system (FCS) is used to select the best forwarding node (BFN) by taking the relative residual energy, link quality and relative distance of the candidate node to the sink node as input variables. In addition, the method also effectively solves the routing hole problem by introducing the flag void_flag.

[0030] A fuzzy logic based underwater acoustic sensor network routing method comprises the following steps:

[0031] (1) The Sink node periodically broadcasts HELLO packets to sense topology changes. The packet structure is as follows: Figure 1 As shown. Each node dynamically maintains a parameter Hcur locally, which is used to indicate the number of hops from the node to the Sink node. The Hcur of the Sink node is set to 0, and the Hcur of other nodes is initialized to 0xFF. All nodes in the entire network are time synchronized. In order to avoid collisions and excessive energy consumption, nodes will only update and forward HELLO packets during the broadcast time. If a node hears a HELLO packet outside the HELLO broadcast time, the packet will be discarded directly. If a node hears a HELLO packet during the HELLO broadcast time, it will extract the ID and hop count (Hcount) from it. If the Hcount in the packet is less than the node's Hcur-1, the node's hop count is updated to Hcount+1, the Hcount in the HELLO packet is updated to Hcount+1, and the HELLO packet is forwarded; otherwise, the HELLO packet is discarded directly. (Hcur represents the hop count of the current node, and Hcount represents the hop count of the previous hop node)

[0032] (2) During the relay selection process, the sending node broadcasts a PING packet.

[0033] (3) After the neighbor node listens to the PING packet, the neighbor node whose hop count from the Sink node is less than or equal to the sending node becomes a candidate node, calculates the link quality between the sending node and the node, and replies to the PONG packet point-to-point.

[0034] (4) Within the waiting time δ, the sending node receives the PONG packet replied from the candidate node and builds the candidate node routing table.

[0035] (5) After the waiting time ends, the best forwarding node is selected based on the candidate node routing table and the fuzzy system. This is mainly divided into three steps: variable fuzzification, fuzzy reasoning based on fuzzy rules, and defuzzification.

[0036] (6) The sending node sets the next hop node ID in the data packet to the output optimal forwarding node ID of the fuzzy system, and then forwards the data packet. The packet structure is as follows: Figure 2 As shown, it contains three parts: header, routing information and payload.

[0037] (7) This method handles the routing hole problem in two ways:

[0038] Use HELLO broadcast to mark the hollow node: the void_flag of all nodes is initialized to 0. During the most recent HELLO packet broadcast, if the node does not receive the HELLO packet, it considers itself a hollow node and sets the void_flag to 1. During the forwarding of data packets, when the neighboring node listens to the PING packet, it first checks the void_flag of the node. If the void_flag is 0, the PONG packet can be sent; if the void_flag is 1, the PONG packet cannot be sent.

[0039] Use information exchange between nodes to mark void nodes: When the source node or current node has data to send, broadcast a PING packet. If the PONG packet is not received from the neighbor node within the waiting time, it is considered to be a void node, and the void_flag is set to 1, and the data packet is re-forwarded to the previous hop node. After receiving the data packet, the previous hop node identifies and extracts the void_flag. If the void_flag is 1, the second priority candidate node is selected to re-forward the data packet.

[0040] by Figure 7 Taking the system composed of underwater wireless sensors as an example, this routing algorithm is explained in detail. The broadcast cycle is defined as the time period from the sending of a HELLO packet to the sending of the next HELLO packet. The broadcast time refers to the actual time used to forward the HELLO packet in each broadcast cycle. During this period, the node will forward the HELLO packet to notify other nodes of its existence and obtain topology information. During the broadcast time of this HELLO broadcast cycle, node 5 did not monitor the HELLO packet, and the void_flag was set to 1, and it was marked as a void node. During the data packet forwarding in this cycle, the network topology changed with the underwater environment. Node 1, node 2, node 3 and the void node are all within the broadcast range of the source node and are neighbor nodes of the source node.

[0041] The specific operation process of the present invention is as follows:

[0042] 1. The sink node periodically broadcasts HELLO packets to sense topology changes. Nodes 1, 2, 3, and 4 listen to the HELLO packets in this cycle and update their hop counts from the sink node. Node 5 does not listen to the HELLO packets, considers itself a hollow node, and sets viod_flag to 1.

[0043] 2. During the relay selection process, if the source node has a data packet to send, it will first broadcast a PING packet.

[0044] 3. Node 1, node 2, node 3 and the hole node are all within the broadcast range of the source node and are neighbor nodes of the source node. After the neighbor node listens to the PING packet, the hole node does not reply to the PONG packet. The neighbor nodes whose hop count from the Sink node is less than or equal to the sending node become candidate nodes. Node 2 and node 3 meet the requirements. They will calculate the link quality between the source node and this node, and reply to the PONG packet point-to-point. Among them, we use the data packet delivery probability model to measure the link quality between nodes. The underwater data packet delivery probability p is modeled as a function of the transmission distance d, the number of bits m and the signal frequency f, and is expressed as: p(d,m,f)=(1-p b (d,f)) m . Where pb(d,f) is the bit error rate, expressed as: Here, P e (X) represents the probability of an error occurring when the average signal-to-noise ratio (SNR) is equal to X under the selected modulation mode. SNR (d, f, X) represents the probability density under given d, f and X, and varies with different fading models. By considering the path loss gain and loss, the average SNR at the receiver is modeled as: Among them, E b represents the energy per bit transmitted, A(d, f) represents the path loss at distance d and frequency f, and N0 represents the noise power density under the additive white Gaussian noise (AWGN) channel. The path loss of the acoustic link can be expressed as: A(d, f) = d k α(f) d Where k∈[1,2] represents the propagation loss factor related to the propagation geometry, and α(f) represents the absorption coefficient, which can be calculated using the Thorpe formula:

[0045] 4. During the waiting time δ, (R is the broadcast range, v is the speed of sound) The source node receives the PONG packets replied by nodes 2 and 3, and builds a candidate node routing table.

[0046] 5. After the waiting time is over, the best forwarding node is selected based on the candidate node routing table and the fuzzy system. It is mainly divided into three steps: variable fuzzification, fuzzy reasoning based on fuzzy rules, and defuzzification.

[0047] Variable fuzzification: In the algorithm, we input membership functions, such as Figure 6 As shown in the figure, the relative residual energy, link quality and relative hop count of the candidate nodes are fuzzified; when establishing the fuzzy subset and membership function, natural experience and expert experience are mainly referred to. The specific parameters and their corresponding feature sets are shown in Table 1.

[0048] Fuzzy reasoning: Then, according to the fuzzy IF-THEN classification rules, the fuzzified input parameters of the candidate nodes are fuzzy reasoned and the memberships of different priorities are obtained. For example, the membership of the candidate node with high relative residual energy is 0.8, the membership of the candidate node with good link quality is 0.7, and the membership of the candidate node with low hop count is 0.6. The membership of the node with high priority is 0.8. The MLFC algorithm contains 17 fuzzy rules, as shown in Table 2.

[0049] Defuzzification: Defuzzification is performed using the centroid method, where the x-axis value of the center point of the area enclosed by the membership function curve and the x-axis is the defuzzification output value, which is also the final output value of the fuzzy algorithm. Its algebraic expression is

[0050] Table 1 Linguistic values ​​of input and output parameters

[0051]

[0052] Table 2 Total fuzzy rules used in fuzzy control

[0053]

[0054]

[0055] 6. Sort the output priorities of the candidate node parameters after the fuzzy system. Candidate node 3 has the highest priority. The source node sets the next hop node ID in the data packet to 3 and then forwards the data packet.

[0056] 7. Node 3 listens to the data packet and finds that it is the next hop node. It receives the data packet and broadcasts a PING packet. However, it does not receive a PONG packet from the candidate node in the waiting time, so it thinks that it is a void node, sets the local void_flag to 1, and then updates the void_flag in the data packet. Then it forwards the data packet to the previous hop node, the source node. After receiving the data packet, the source node sets the void_flag in the data packet to 0, and then forwards it to the second best forwarding node, node 2.

[0057] 8. Repeat the above process to forward the data packet to the Sink node on the water surface.

Claims

1. A fuzzy logic based underwater acoustic sensor network routing method, the data packets used include HELLO packets, PING packets and PONG packets, wherein: The PING packet contains: the sending node ID, the next hop node ID and the number of hops from the Sink node; The PONG packet contains: the sending node ID, the next hop node ID, the remaining energy of the candidate node, the link quality and the number of hops from the sink node; The underwater acoustic sensor network routing method comprises the following steps: (1) Sink nodes periodically broadcast HELLO packets to sense topology changes. Each node dynamically maintains a parameter Hcur representing the hop count of the node locally, which is used to represent the hop count from the node to the sink node. All nodes in the entire network are time synchronized. If a node hears a HELLO packet within the HELLO broadcast time, it extracts the sending node ID and the hop count Hcount from the sink node. If the Hcount in the packet is less than the Hcur-1 of this node, the hop count of the node is updated to Hcount+1, the Hcount in the HELLO packet is updated to Hcount+1, and the HELLO packet is forwarded. Otherwise, the HELLO packet is directly discarded. (2) During the relay selection process, the sending node broadcasts a PING packet; (3) After the neighbor node listens to the PING packet, the neighbor node whose hop count from the Sink node is less than or equal to the sending node becomes the candidate node. The candidate node calculates the link quality between the sending node and the node, and replies with a PONG packet point-to-point; (4) During the waiting time, the sending node receives the PONG packet replied from the candidate node and builds the candidate node routing table; (5) after the waiting time ends, selecting the best forwarding node based on the candidate node routing table and the fuzzy system; (6) The sending node sets the next hop node ID in the data packet as the output optimal forwarding node ID of the fuzzy system, and then forwards the data packet. The data packet structure contains three parts: header, routing information and data payload; among which, the routing information includes the next hop node ID, forwarding times and routing void_flag.

2. The underwater acoustic sensor network routing method based on fuzzy logic according to claim 1 is characterized in that: The following methods are used to solve the routing hole problem: Use HELLO broadcast to mark the void node: the void_flag of all nodes is initialized to 0; during the most recent HELLO packet broadcast, if the node does not receive the HELLO packet, it considers itself a void node and sets the void_flag to 1; during the forwarding of data packets, when the neighbor node listens to the PING packet, it first checks the void_flag of the node; if the void_flag is 0, the PONG packet can be sent; if the void_flag is 1, the PONG packet cannot be sent; Use information interaction between nodes to mark void nodes: When the source node or the current node has data to send, it broadcasts a PING packet; if it does not receive a PONG packet from a neighboring node within the waiting time, it considers itself a void node, sets void_flag to 1, and re-forwards the data packet to the previous hop node; after receiving the data packet, the previous hop node identifies and extracts void_flag; if void_flag is 1, the second priority candidate node is selected to re-forward the data packet.

3. The underwater acoustic sensor network routing method based on fuzzy logic according to claim 1 is characterized in that: The packet delivery probability model is used to measure the link quality between nodes.

4. The underwater acoustic sensor network routing method based on fuzzy logic according to claim 3 is characterized in that: The method of using the packet delivery probability model to measure the link quality between nodes is as follows: The underwater packet delivery probability p is modeled as a function of the transmission distance d, the number of bits m, and the signal frequency f, and is expressed as: p(d,m,f)=(1-p b (d,f)) m ; Among them, p b (d,f) is the bit error rate; f SNR (d, f, X) represents the probability density at a given transmission distance d, signal frequency f, and average signal-to-noise ratio X. By considering the path loss gain and loss, the average signal-to-noise ratio SNR at the receiving end is modeled as: Among them, E b represents the energy per bit transmitted, A(d,f) represents the path loss of the transmission distance d and the signal frequency f, and N0 represents the noise power density under the additive white Gaussian noise (AWGN) channel; the path loss of the acoustic link is expressed as: A(d,f) = d k α(f) d ; where k∈[1,2] represents the propagation loss factor related to the propagation geometry, and α(f) represents the absorption coefficient.

5. The underwater acoustic sensor network routing method based on fuzzy logic according to claim 1 is characterized in that: The fuzzy system includes three steps: variable fuzzification, fuzzy reasoning according to fuzzy rules, and defuzzification; In variable fuzzification, the residual energy, link quality and relative hop count of candidate nodes are fuzzified according to the input membership function.

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