CN111278079A - Hierarchical cooperative routing method and system for underwater self-organizing network - Google Patents

Abstract

The invention discloses a layered cooperative routing method and system for an underwater self-organizing network. The nodes in the underwater self-organizing network cluster forward the collected data to the corresponding cluster head node, and the cluster head node transmits the data to the upper-layer cluster. The head node, the last cluster head node forwards the data to the sink node through the nodes of the water layer; the nodes in the cluster forward the collected data to the corresponding cluster head node, and the nodes participating in the communication are set as: source node, middle node The relay node and the destination node; the source node broadcasts to the relay node and the destination node at the same time, the threshold value is pre-judged at the destination node, and the noise threshold is used to judge the quality of the transmitted signal; if the received signal quality at the destination node is lower than the noise gate The limit value will start the relay node for cooperative transmission of data. The method improves the data transmission rate and survivability of the network, and the formed system provides an important guarantee for the application of the underwater self-organizing network in the actual seabed observation network.

Description

Hierarchical cooperative routing method and system for underwater self-organizing network

technical field

The present disclosure relates to the technical field of underwater self-organizing networks, and in particular, to a hierarchical cooperative routing method and system for underwater self-organizing networks.

Background technique

The statements in this section merely mention background related to the present disclosure and do not necessarily constitute prior art.

The ocean has a vast area and many resources, and the exploration of the ocean has become a hot research topic today. With the development of science and technology, the self-organizing network has been sufficiently adapted to the underwater environment to form an underwater underwater self-organizing network. The underwater self-organizing network is usually used in the kelp observation network, mainly in the deep water environment. Because the radio waves will be absorbed by the seawater and attenuate rapidly, underwater acoustic communication is usually used. Underwater acoustic signals have long end-to-end delays and limited bandwidth due to attenuation, so high-quality underwater routing mechanisms are a major concern for research. During underwater data transmission, the data signal suffers from fading and path loss, fails to reach the destination successfully or has a high bit error rate.

In the process of realizing the present disclosure, the inventor found that the following technical problems exist in the prior art:

There are many types of underwater routing protocols, which are divided into cooperative routing protocols and universal routing protocols according to whether to join the cooperation mechanism. Regarding universal routing, depth-based DBR (Depth Based Routing) is one of the classic algorithms. It senses the depth of nodes as the basis for forwarding. The algorithm is simple and easy to understand but consumes a lot of energy. Therefore, S. Gul et al. proposed a Lightweight Deep Routing Protocol (LDBR) to minimize energy consumption, but without adding routing fault tolerance and recovery algorithms. Considering the cross-layer transmission, J. Liu et al. proposed an energy-saving cross-layer routing protocol (RECRP), which does not need to consider the node location to save energy, but does not consider the link transmission quality. S.H.Ahmed proposed an intelligent protocol for directional flooding, including angle adaptation and threshold adaptation to dynamically reflect QoS requirements, but increased communication overhead. Z. Jianan et al. proposed a routing protocol based on vector and energy, which determines the priority according to the distance of the vector; and then forwards with energy without considering the number of nodes. Regarding cooperative routing, using relay nodes and master nodes for data transmission from source to sink improves transmission reliability and data integrity but also increases network energy consumption. S. Ahmed et al. proposed an adaptive cooperative protocol, where nodes match a unidirectional antenna to cooperatively transmit to reduce network overhead but increase end-to-end delay. T. Tayyaba et al. reduced the energy consumption of cooperative communication by introducing a mobile sink node. Since the relay selection seriously affects the network performance, this limitation needs to be further overcome. A. Ahmad et al. proposed a cooperative energy-saving routing protocol (Co-EEUWSN), which jointly optimizes the transmission power of the physical layer and the network layer, which improves the arrival rate of data but introduces noise problems. To sum up, there is an urgent need for a more suitable underwater self-organizing network routing method that comprehensively considers issues such as energy consumption, signal-to-noise ratio, and transmission rate to be applied in seabed observation networks.

SUMMARY OF THE INVENTION

In order to solve the deficiencies of the prior art, the present disclosure provides a layered cooperative routing method and system for an underwater self-organizing network;

In a first aspect, the present disclosure provides a hierarchical cooperative routing method for underwater self-organizing networks;

A hierarchical cooperative routing method for underwater ad hoc networks, including:

Part of the nodes of the underwater self-organizing network are divided into cluster head nodes and intra-cluster nodes; the intra-cluster nodes cooperate and communicate with each other, and forward the collected data to the corresponding cluster head nodes. The cluster head nodes integrate the data and transmit the data. For the cluster head node on the upper layer, after layer-by-layer forwarding, the last cluster head node transmits the data to the node on the water surface layer, and the node on the water surface layer forwards the data to the nearest sink node on the water surface;

The nodes in the cluster communicate with each other in cooperation, and forward the collected data to the corresponding cluster head node, including: setting the nodes participating in the communication as: a source node, a relay node and a destination node;

The source node broadcasts to the relay node and the destination node at the same time, performs threshold pre-judgment at the destination node, and uses the noise threshold to judge the quality of the transmission signal;

If the quality of the signal received at the destination node is lower than the noise threshold, the relay node will start the cooperative transmission of data.

In a second aspect, the present disclosure also provides a hierarchical cooperative routing system for underwater self-organizing networks;

A hierarchical cooperative routing system for underwater ad hoc networks, including:

The cluster head node and the intra-cluster nodes are deployed on the underwater self-organizing network. The cluster area is selected for each layer, and the cluster head node is elected for each cluster area; each cluster area includes a cluster head node and several intra-cluster nodes. The nodes in the cluster cooperate and communicate with each other, and forward the collected data to the corresponding cluster head node. The cluster head node integrates the data and transmits it to the cluster head node on the upper layer. A cluster head node transmits data to the nodes on the water surface layer, and the nodes on the water surface layer forward the data to the nearest sink node on the water surface;

The nodes in the cluster communicate with each other in cooperation, and forward the collected data to the corresponding cluster head node, including: setting the nodes participating in the communication as: a source node, a relay node and a destination node;

The source node broadcasts to the relay node and the destination node at the same time, performs threshold pre-judgment at the destination node, and uses the noise threshold to judge the quality of the transmission signal;

If the quality of the signal received at the destination node is lower than the noise threshold, the relay node will start the cooperative transmission of data, that is, backup and retransmit the data packet.

Compared with the prior art, the beneficial effects of the present disclosure are:

1. Aiming at the stability and energy consumption of the underwater self-organizing network, the present disclosure proposes a hierarchical cooperative routing method. Using cooperative routing to improve the accuracy of arriving packets, hierarchical routing also balances energy consumption issues.

2. The relay cooperation based on cooperative routing is added to the data transmission stage, so that the source node can send the same data through multiple paths, so that the target node can receive data packets with low bit error rate. Compared with traditional layered protocols, cooperative routing can replace ordinary multi-hop transmission and better ensure the link quality of underwater channels.

3. Average clustering algorithm is used to cluster nodes, while conditional probability can be used to select cluster heads. In the process of data transmission, the relay node amplifies the signal and backs up the data packets to avoid packet loss, thereby improving the data transmission rate and survivability of the network, and providing a practical solution for the application of the underwater self-organizing network to the actual seabed observation network. Important Guarantee.

Description of drawings

The accompanying drawings that form a part of the present application are used to provide further understanding of the present application, and the schematic embodiments and descriptions of the present application are used to explain the present application and do not constitute improper limitations on the present application.

Fig. 1 is the underwater self-organizing network model of the first embodiment;

Fig. 2 is the underwater cooperative routing model of the first embodiment;

Fig. 3 is the intra-cluster cooperation routing diagram of the first embodiment;

4 is a schematic diagram of relay/destination node selection in the first embodiment;

FIG. 5 is a flow chart of the method of the first embodiment.

Detailed ways

It should be noted that the following detailed description is exemplary and intended to provide further explanation of the application. Unless otherwise defined, all technical and scientific terms used in this disclosure have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

It should be noted that the terminology used herein is for the purpose of describing specific embodiments only, and is not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly dictates otherwise, the singular is intended to include the plural as well, furthermore, it is to be understood that when the terms "comprising" and/or "including" are used in this specification, it indicates that There are features, steps, operations, devices, components and/or combinations thereof.

Embodiment 1, this embodiment provides a hierarchical cooperative routing method for an underwater self-organizing network;

A hierarchical cooperative routing method for underwater ad hoc networks, including:

Part of the nodes of the underwater self-organizing network are divided into cluster head nodes and intra-cluster nodes; the intra-cluster nodes cooperate and communicate with each other, and forward the collected data to the corresponding cluster head nodes. The cluster head nodes integrate the data and transmit the data. For the cluster head node on the upper layer, after layer-by-layer forwarding, the last cluster head node transmits the data to the node on the water surface layer, and the node on the water surface layer forwards the data to the nearest sink node on the water surface;

The nodes in the cluster communicate with each other in cooperation, and forward the collected data to the corresponding cluster head node, including: setting the nodes participating in the communication as: a source node, a relay node and a destination node;

The source node broadcasts to the relay node and the destination node at the same time, performs threshold pre-judgment at the destination node, and uses the noise threshold to judge the quality of the transmission signal;

If the quality of the signal received at the destination node is lower than the noise threshold, the relay node will start the cooperative transmission of data.

Further, dividing part of the nodes of the underwater self-organizing network into cluster head nodes and intra-cluster nodes, the specific steps include:

S1: Deploy sensor nodes underwater to form an underwater self-organizing network;

S2: Divide the underwater self-organizing network into several layers. The layer closest to the water surface is the water surface layer. The nodes in the water surface layer are not divided into cluster areas. Cluster areas are selected for each layer of the non-water surface layer. The area elects the cluster head node; each cluster area contains a cluster head node and several intra-cluster nodes.

Further, the method further includes: after completing a round of data transmission, the cluster head node CH will determine its own cluster average energy (if the energy is less than the network threshold energy) according to the remaining energy of the cluster members, then the cluster will This layer is reconstructed and the cluster head node CH will be re-elected. Routing information is also updated.

Further, in the S1, sensor nodes are deployed underwater to form an underwater self-organizing network; the specific steps include:

The sensor nodes are randomly anchored underwater to form a self-organizing network.

Further, each sensor node is further provided with a depth sensor, and the depth sensor is used to detect the depth at which the current sensor node is located underwater.

Further, in the S2, the underwater self-organizing network is divided into several layers, and the specific steps include:

According to the set communication radius, the underwater self-organizing network is divided into several layers.

Further, in the S2, the underwater self-organizing network is divided into several layers, and the specific steps include:

LN=D _area /W (1)

Among them, LN represents the number of layers; D _area represents the depth of the monitoring area, and W represents the communication diameter of the sensor node;

Among them, N _num represents the serial number of the layer where the sensor node is located, and N _dpt represents the depth where the sensor node is located.

Further, in the step S2, selecting a cluster area for each layer of the non-water surface layer is specifically: using a clustering algorithm to select a cluster area for each layer of the non-water surface layer.

Further, the clustering algorithm is used to select the cluster area for each layer of the non-water surface layer, and the specific steps include:

S201: Select a node as the initial cluster center K ₁ , and the node farthest from K ₁ as the second cluster center K ₂ ;

S202: Select the node farthest from both K ₁ and K ₂ as the third cluster center K ₃ , where K ₃ is the largest among min(d(K ₃ , K ₁ ), d(K ₃ , K ₂ )) value;

Select the node farthest from K ₁ , K ₂ and K ₃ as the fourth cluster center K ₄ , select min(d(K ₄ , K ₁ ), d(K ₄ , K ₂ ), d(K ₄ , K ₃ )) in the maximum value as K ₄ ;

By analogy, all K cluster centers are selected;

S203: After obtaining the K initial cluster centers, use an average clustering algorithm to cluster the sensor nodes of each layer to obtain a cluster area.

Further, in the S2, the cluster head node is elected for each cluster area, specifically: using the Bayesian formula to elect the cluster head.

Further, using the Bayesian formula to elect cluster heads, the specific steps include:

S211: Calculate the Bayesian probability according to the remaining energy, energy consumption rate and link quality of each sensor node in the cluster;

S212: For nodes greater than or equal to the Bayesian probability, it is regarded as a cluster head node;

S213: For nodes less than the Bayesian probability, it is regarded as a node in the cluster.

It should be understood that the Bayesian probability is calculated according to the remaining energy, energy consumption rate, link quality and other attribute values of each sensor node in the cluster, and the Bayesian probability is:

Among them, P _i is the posterior probability of the i-th node being elected as the cluster head, P _ij is the probability of the j-th attribute of the i-th node, and a is the number of node attributes.

Further, the method further includes: if the quality of the signal received at the destination node is higher than the noise threshold, transmitting directly.

Further, the quality of the signal received at the destination node is the ratio of the power value of the signal received at the destination node to the noise power value.

Further, if the signal quality received at the destination node is lower than the noise threshold, the relay node will be started to perform cooperative data transmission, which is expressed as:

y _RD (f)=αy _SR (f)g _RD +n _RD (f) (4)

y _D =y _SD (f)+y _RD (f) (5)

E_b为传输的信号能量，N₀为噪声的功率谱密度。Among them, α is the amplification factor, set

E _b is the transmitted signal energy, and N ₀ is the power spectral density of the noise.

Further, the selection criteria of the relay node and the destination node are:

In the process of data transmission, each node obtains its own depth information and the depth information of other nodes, and stores the nearest node to its own neighbor node set;

The relay node and the destination node are selected based on the Signal-Noise-Ratio (SNR) criterion.

Further, the selection of the relay node and the destination node based on the SNR standard specifically includes:

The depth reference d _th is pre-set, and m sensor nodes with the highest residual energy within the boundary specified by d _th are selected as candidate relay nodes;

Select the n sensor nodes that are located outside the boundary specified by d _th and have the highest residual energy as candidate destination nodes;

From the candidate destination nodes, filter out the final destination node;

After the final destination node is selected, the final relay node is selected from the candidate relay nodes by combining the depth difference between the source node and the destination node.

The final destination node is screened out from the candidate destination nodes; the selection function is:

The v _D corresponding to the maximum value of f(v _D ) is the optimal destination node.

After the final destination node is selected, the final relay node is selected from the candidate relay nodes in combination with the depth difference between the source node and the destination node; the selection function is:

所覆盖的节点数与传输半径区域内的节点数之比，表示为

f(v_R)最大值对应的v_R即为最优中继节点。Among them, f(v _D ) is the destination node v _d selection function, f(v _R ) is the relay node selection function, ρ _D is the destination node density, that is, the ratio of the number of nodes covered by the transmission radius to the number of nodes in this layer, which means is ρ _D =N _r /N _i . ρ _R is the density of relay nodes, that is, the set depth value

The ratio of the number of nodes covered to the number of nodes in the transmission radius area, expressed as

The v _R corresponding to the maximum value of f(v _R ) is the optimal relay node.

Underwater network model:

For underwater ad hoc networks, the main goals of routing protocol design are to reduce network energy consumption and increase throughput. Sensor nodes deployed underwater are energy constrained and batteries are difficult to replace. In terms of energy saving, cluster-based approaches are proven feasible. The present disclosure first determines an underwater network model, as shown in FIG. 1 , and divides the network in a hierarchical manner. Sensor nodes are arbitrarily anchored in an underwater ad hoc network. The depth information of each node can be known, obtained through the depth sensor installed on the node. Considering the energy balance, the nodes close to the water surface are not clustered and are defined as the water surface layer. The main job of the water surface layer is to forward the data packets transmitted by the underwater cluster head to the sink node. Other nodes perform network layering according to a given communication radius, and each cluster includes a cluster head node (CH) and multiple intra-cluster nodes. The nodes in the cluster cooperate and communicate with each other and are finally forwarded to the cluster head, and the cluster head node forwards the information to the nearest sink node layer by layer after information fusion. At the gathering node on the water surface, underwater acoustic communication is used underwater, and radio communication can be used on the water surface. When all nodes complete the transmission to the sink node, it is a cycle, which is defined as one round.

Underwater collaborative routing model:

In underwater self-organizing networks, the environment is complex, and direct communication between nodes may be lost due to the influence of seawater currents, or may be hindered by plankton. Therefore, collaboration is an effective way to avoid such problems. As shown in Figure 2, the cooperative routing model consists of a source node, a destination node and a relay node. The source node broadcasts to the relay node and the destination node at the same time, performs threshold pre-judgment at the destination node, and uses the SNR noise threshold γ ₀ to judge the quality of the transmitted signal. If the quality of the signal received at the destination node is lower than the threshold value, the relay node will be activated for cooperative transmission. Considering the problem of saving node energy, it is stipulated that each relay node can only retransmit once.

In the first stage of cooperative routing: the source node first broadcasts to the relay node and the destination node.

y _SR (f) = x _S g _SR + n _SR (f), y _SD (f) = x _S g _SD +n _SD (f) (8)

Underwater acoustic communication is easily affected by a variety of noise sources, such as seabed turbulence, ship motion, wind waves, and turbulence. Considering these factors, the present disclosure gives the following general underwater noise formula:

n(f)=n _T (f)+n _S (f)+n _W (f)+n _Th (f) (9)

in:

Table 1. Definition of parameters related to underwater cooperative routing

In the second stage of cooperative routing: the destination node firstly performs an initial judgment of the threshold γ0, and informs the relay node (the selection of the relay node will be given in the following part) for the signal lower than the threshold value to perform cooperative retransmission, and relay transmission. Amplify-and-forward is used to perform maximum ratio combining at the destination node. The received direct transmission signal ySD is expressed as follows:

|g_SD|是符合瑞利分布的衰落幅值，g～(0,σ²)，σ²＝E[|g_SD|²]＝1，θ_SD是相位。于是在目的节点处接收到的功率为The complex channel fading experienced between nodes can be expressed in complex form:

|g _SD | is the fading amplitude conforming to the Rayleigh distribution, g∼(0,σ ² ), σ ² =E[|g _SD | ² ]=1, and θ _SD is the phase. So the power received at the destination node is

At this point, the signal-to-noise ratio (SNR) threshold is judged:

where P _n represents the noise power.

If the γ _SD at this time is lower than the set initial value γ ₀ , the cooperative routing is performed, which is expressed as follows:

y _RD (f)=αy _SR (f)g _RD +n _RD (f) (4)

y _D =y _SD (f)+y _RD (f) (5)

E_b为传输信号的能量，N₀为噪声的功率谱密度。Among them, α is the amplification factor, set

E _b is the energy of the transmitted signal, and N ₀ is the power spectral density of the noise.

The complete process of the underwater hierarchical cooperative routing algorithm:

For underwater self-organizing networks, energy consumption is usually a pressing issue. Due to the corrosive nature of seawater, underwater nodes are often corroded and cannot be recycled, and it is difficult to replace batteries. The present disclosure rationally optimizes network consumption by building an appropriate underwater energy model. The underwater routing protocol needs to solve the communication problem caused by the dynamic network topology, and the seawater flow affects the communication between nodes. Secondly, the point-to-point node communication is not stable enough, and there is a problem of packet loss, and the quality of the link will affect the performance of the entire network. Therefore, the present disclosure proposes a layered routing protocol based on cooperation, which utilizes collaborative routing to improve the accuracy of arriving data packets, and simultaneously balances the problem of energy consumption by layered routing. The whole protocol is divided into two phases: the layering phase and the transmission phase. The hierarchical phase is responsible for network partitioning and node clustering, and the transport phase is responsible for cooperative routing and data forwarding. These two phases are described in detail below:

Network layering stages:

Considering the energy balance, the monitoring network is divided into layers of the same size. The number of layers LN can be calculated by LN=D _area /W, where D _area represents the depth of the monitoring area, and W=2×r represents the coverage area with the communication radius of the node. The first layer is defined as the water surface layer, which does not cluster nodes in the layer, and directly transmits information to the nearest sink node. Each sensor node is equipped with a depth sensor, and the depth of the node is sensed by the sensor itself, so the number of layers (that is, the layer serial number) where each node is located is obtained as follows:

Among them, N _num represents the serial number of the layer where the node is located, and N _dpt represents the depth where the node is located.

After repeating the above calculation, the layer sequence number of each node will be obtained and stored in the data packet list. At this point, all layers are completed.

Next, the present disclosure introduces in detail the process of using the average clustering algorithm to select the cluster region and the Bayesian formula to elect the cluster head node (CH).

Assuming that in an ideal environment, there are K initial cluster centers in each layer, and the total number of nodes is N, then the total number of nodes in each layer N _i =N/LN, where i∈{2,...,LN }.

Ideally, the optimal number of K is defined as:

Among them, W is the node communication range, and L×L×L is the monitoring network range.

Considering the uneven distribution of nodes, this algorithm selects the initial cluster center according to the density ρ of surrounding nodes (the ratio of the number of nodes within the induction radius to the total number of nodes). First select a node as the initial cluster center K ₁ , and the node farthest from K ₁ as the second cluster center K ₂ . Then the node farthest from both K ₁ and K ₂ is selected as the third cluster center K ₃ , which is the maximum value among min(d(K ₃ , K ₁ ), d(K ₃ , K ₂ )). The maximum value of min(d(K ₄ , K ₁ ), d(K ₄ , K ₂ ), d(K ₄ , K ₃ )) is selected as K ₄ . Finally, all K cluster centers are selected according to the above rules. Note that each layer selects the cluster area in this way until all are selected.

After obtaining the K initial cluster centers, the network is clustered using an average clustering algorithm, where the variance (sum of squared errors in the clusters) is used as a standard metric function, which can be defined as:

Among them, x∈R _i indicates that the node sending distance is within the communication range, X indicates the distance between the node and the sink node, and X _i is the k cluster area in i∈{1,2,.....,k} in-depth information.

The convergence region is defined as follows:

|E ₁ -E ₂ |<ε (16)

Among them, ε is the minimum value. E ₁ represents the current metric function, and E ₂ represents the previous round of metric functions. Use the standard metric function to judge whether the clustered area meets the requirements of the convergence area, and if not, re-divide the area until the conditions are met.

Next, use the Bayesian formula to elect cluster heads. First, each node calculates its own effective time H _t , and synthesizes the cluster head election time Ti and remaining energy. H _t is obtained by the following formula:

where δ[1, 0.5] represents an arbitrary value that avoids the collision of nodes with similar residual energy, _Er refers to its residual energy, and E ₀ refers to its initial energy. It can be seen from the above formula that the higher the residual energy, the shorter the effective time and the greater the possibility of being elected as the cluster head. The node is elected as the cluster head within H _t , and automatically gives up the competition for the cluster head after the specified time.

The Bayesian probability is calculated based on the properties of each node's remaining energy, energy consumption rate, and link quality.

The calculation results in two cases: the node n _i is the cluster head probability P(n _i =H), or the cluster member probability P(n _i =H').

The present disclosure calculates the probability of being cluster head nodes of each other in the cluster, and this maximum probability is based on their attribute values.

The prior probability P (n _i =H) of the node being elected as a cluster head without knowing the attributes of the node, and the posterior probability P of being elected as the cluster head under the premise of knowing the remaining energy, energy consumption rate and link quality of the node (n _i =H|x _ij ), x _ij represents the j-th attribute of the i-th node x _i . Similarly, there are P(n _i =H') and P(n _i =H'|x _ij ) and the probability P(x _ij ) of the node attribute set.

P(x _ij | _ni =H)=(P( _ni =H|x _ij )*P(x _ij ))/P( _ni =H) (18)

Now, there are only two cases: become H or H'.

P( _ni =H|x _ij )+P( _ni =H'|x _ij )=1 so that P( _ni =H)+P( _ni =H')=1.

Assuming a known cluster is not a cluster head node, the posterior probability that a cluster has a set of possible attribute values is:

For convenience of expression later, x _i1 , x _i2 ,..., x _ia =X _i is the attribute value set of this node. According to the above formula, the following two formulas can be obtained:

Next, the attribute set X _i is known by the data packet, and the probability of this node becoming the cluster head is:

Since a set of attributes X _i about a node is given, it can be in H or H' state:

P(X _i )=P(X _i |n _i =H)*P(n _i =H)+P(X _i | _{ni =H′)*P(n i =} H′) (23)

Therefore, the probabilities of these two states appearing are equal, so combining the above formulas, the probability of a node becoming a cluster head is as follows:

Simplifying the above formula, P _i is the posterior probability that the node is elected as the cluster head, and P _ij is the probability that the attributes of the node are known

进行对数分析可得：The present disclosure performs a reciprocal analysis on the above formula, and then eliminates the

Logarithmic analysis yields:

Then according to the logarithmic property, we can get:

So, _Pi is:

则

Among them, P _i is the posterior probability of the i-th node being elected as the cluster head, P _ij is the probability of the j-th attribute of the i-th node, and a is the number of node attributes. make

but

Set P _i , each cluster area is selected according to this probability, and the execution is repeated until the selection of each layer is completed.

Network transfer stage:

In the underwater acoustic communication network, because the propagation rate of the underwater acoustic signal is much lower than that of the radio wave, the underwater propagation delay is greatly increased, and the data packets will have collision problems in the same time slot. Secondly, the propagation of sound waves in water will have the effect of Doppler scaling, resulting in the spread of the transmitted signal, and the transmission will not be within the specified range. The present disclosure considers the characteristics of the underwater acoustic channel, assumes that the transmitted data is modulated by QPSK, and adopts OFDM to mitigate inter-symbol interference. The focus of the present disclosure is to improve the intra-cluster transmission mode. Different from the traditional underwater transmission, it is considered to join the cooperative routing, and use the cooperative transmission composed of the source node and the relay node to perform the backup and retransmission operation.

As shown in Figure 3, in the data transmission stage, each node first broadcasts to obtain the depth information of itself and other nodes, and stores the nearest node (measured by the depth difference between the two nodes) to its neighbors. node set. Next, select the relay node and the destination node. In traditional cooperative routing, generally only the depth and remaining energy of the node are considered to select the relay node. Therefore, it is not assumed how the relay node should choose when the quality of the transmission link is lower than normal transmission. Therefore, it is more reliable in the present disclosure to select the relay node based on the signal-to-noise ratio (SNR) criterion.

In the present disclosure, a depth reference d _th is preset, and 3/4 of the transmission radius is d _th , and the relay node is located within the boundary specified by d _th and has the highest residual energy. The target node is the node that is outside the boundary specified by d _th and has the highest remaining energy.

Then, the present disclosure filters out more suitable relay nodes and destination nodes in combination with the node's own depth, surrounding node density and SNR criteria. After selecting a partner node, perform collaborative routing. As shown in Figure 4, the partner node selection graph.

First select the destination node, and then combine the depth difference D _SD between the source node and the destination node to give the relay node selection formula:

Among them, f(v _D ) is the destination node selection function, and f(v _R ) is the relay node selection function.

所覆盖的节点数与传输半径区域内的节点数之比，表示为

ρ _D is the ratio of the destination node density, that is, the number of nodes covered by the transmission radius to the number of nodes in the layer, expressed as ρ _D =N _r /N _i . ρ _R is the density of relay nodes, that is, the set depth value

The ratio of the number of nodes covered to the number of nodes in the transmission radius area, expressed as

The link quality is judged by the SNR standard, which is expressed as:

After the selection of the relay node is successful, the present disclosure will wait and verify at the destination node whether the quality of the direct transmission link at this time meets the threshold value, otherwise the relay node is used to perform the backup retransmission operation. The cooperative communication between nodes in the cluster is transmitted layer by layer until the last target node is CH. Before sending the data packets to the CH, the data fusion has been done at the destination node, which reduces the processing tasks of the CH. The CH is only responsible for transmitting data to the water surface, and the surface nodes directly transmit to the sink node. Compared with non-cooperative protocols, intra-cluster cooperation can ensure the reliability of data transmission, and preprocessing can reduce the burden of CH and network interruption time. The collaborative routing diagram is shown in Figure 5, along with the proposed protocol flow chart.

After completing a round, the CH will determine its own cluster average energy based on the remaining energy of the cluster members (if this energy is less than the network threshold energy), the cluster will restructure at this layer and the CH will be re-elected. Routing information is also updated.

The present disclosure proposes a layered cooperative routing method for underwater self-organizing networks. By adding a relay cooperative model based on cooperative routing to the data transmission stage, the source node can send the same data through multiple paths. , the target node receives the low bit error rate data packet. Compared with traditional layered protocols, cooperative routing can replace ordinary multi-hop transmission and better ensure the link quality of underwater channels. The average clustering algorithm is used to cluster nodes, while conditional probabilities can be used to select cluster heads. In the process of data transmission, the relay node amplifies the signal and backs up the data packets to avoid packet loss, thereby improving the data transmission rate and survivability of the underwater self-organizing network, and applying the underwater self-organizing network to the actual seabed observation. An important guarantee is provided in the network.

Embodiment 2, this embodiment also provides a layered cooperative routing system oriented to an underwater self-organizing network;

A hierarchical cooperative routing system for underwater ad hoc networks, including:

The cluster head node and the intra-cluster nodes are deployed on the underwater self-organizing network. The cluster area is selected for each layer, and the cluster head node is elected for each cluster area; each cluster area includes a cluster head node and several intra-cluster nodes. The nodes in the cluster cooperate and communicate with each other, and forward the collected data to the corresponding cluster head node. The cluster head node integrates the data and transmits it to the cluster head node on the upper layer. A cluster head node transmits data to the nodes on the water surface layer, and the nodes on the water surface layer forward the data to the nearest sink node on the water surface;

The nodes in the cluster communicate with each other in cooperation, and forward the collected data to the corresponding cluster head node, including: setting the nodes participating in the communication as: a source node, a relay node and a destination node;

The source node broadcasts to the relay node and the destination node at the same time, performs threshold pre-judgment at the destination node, and uses the noise threshold to judge the quality of the transmission signal;

If the quality of the signal received at the destination node is lower than the noise threshold, the relay node will start the cooperative transmission of data.

The above descriptions are only preferred embodiments of the present application, and are not intended to limit the present application. For those skilled in the art, the present application may have various modifications and changes. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of this application shall be included within the protection scope of this application.

Claims (10)

1. The layered cooperative routing method for the underwater self-organizing network is characterized by comprising the following steps:

dividing partial nodes of the underwater self-organizing network into cluster head nodes and cluster internal nodes; the cluster nodes are mutually cooperated and communicated, the collected data are forwarded to the corresponding cluster head nodes, the cluster head nodes integrate the data and transmit the data to the cluster head nodes on the upper layer, after the data are forwarded layer by layer, the last cluster head node transmits the data to the nodes on the water surface layer, and the nodes on the water surface layer forward the data to the nearest sink node on the water surface;

the cluster nodes are mutually cooperated and communicated, and the collected data is forwarded to the corresponding cluster head node, and the method comprises the following steps: the nodes participating in the communication are set as follows: a source node, a relay node and a destination node;

the source node broadcasts to the relay node and the destination node at the same time, threshold value prejudgment is carried out at the destination node, and the quality of a transmission signal is judged by utilizing a noise threshold;

and if the quality of the signal received by the destination node is lower than the noise threshold value, the relay node is started to carry out cooperative transmission of the data.

2. The method as claimed in claim 1, wherein the dividing of the partial nodes of the underwater ad-hoc network into cluster head nodes and intra-cluster nodes comprises the following steps:

s1: deploying sensor nodes underwater to form an underwater self-organizing network;

s2: dividing the underwater self-organizing network into a plurality of layers, wherein the layer closest to the water surface is a water surface layer, nodes in the water surface layer do not divide a cluster region, a cluster region is selected for each layer other than the water surface layer, and a cluster head node is selected for each cluster region; each cluster area comprises a cluster head node and a plurality of cluster nodes.

3. The method of claim 1, further comprising: after completing one round of data transmission, the cluster head node CH determines its own cluster average energy according to the remaining energy of the cluster members, if the own cluster average energy is less than the network threshold energy, the cluster is reconstructed at the layer, and the cluster head node CH is reselected; the routing information is also updated.

4. The method of claim 2, wherein the underwater ad hoc network is divided into a plurality of layers, comprising the steps of:

and dividing the underwater self-organizing network into a plurality of layers according to the set communication radius.

5. The method of claim 2, wherein the cluster regions are selected for each of the non-aqueous layers by: and selecting cluster regions for each layer of the non-water surface layer by adopting a clustering algorithm.

6. The method as claimed in claim 2, wherein the selecting of the cluster head node for each cluster region is specifically: and (4) selecting the cluster head by using a Bayesian formula.

7. The method of claim 6, wherein a bayesian formula is used to elect a cluster head, comprising the steps of:

s211: calculating Bayes probability according to the residual energy, the energy consumption rate and the link quality of each sensor node in the cluster;

s212: regarding the nodes with the Bayesian probability being larger than or equal to the Bayesian probability as cluster head nodes;

s213: and regarding the nodes with the probability less than the Bayesian probability as the nodes in the cluster.

8. The method of claim 1, wherein the selection criteria for the relay node and the destination node are:

each node acquires own depth information and depth information of other nodes in the data transmission process, and stores the node closest to the node to the neighbor node set of the node;

the relay node and the destination node are selected based on a signal-to-noise ratio criterion.

9. The method of claim 8, wherein selecting the relay node and the destination node based on the SNR criterion comprises:

the depth reference d is preset_thSelection is at d_thM sensor nodes with the highest residual energy simultaneously in a specified boundary are used as candidate relay nodes;

is selected to be located at d_thN sensor nodes with the highest residual energy outside the specified boundary are used as candidate destination nodes;

screening out a final destination node from the candidate destination nodes;

and after the final destination node is selected, the final relay node is screened out from the candidate relay nodes by combining the depth difference between the source node and the destination node.

10. The layered cooperative routing system facing the underwater self-organizing network is characterized by comprising:

cluster head nodes and cluster internal nodes are deployed on the underwater self-organizing network, cluster areas are selected for each layer, and cluster head nodes are selected for each cluster area; each cluster area comprises a cluster head node and a plurality of cluster nodes; the cluster nodes are mutually cooperated and communicated, the collected data are forwarded to the corresponding cluster head nodes, the cluster head nodes integrate the data and transmit the data to the cluster head nodes on the upper layer, after the data are forwarded layer by layer, the last cluster head node transmits the data to the nodes on the water surface layer, and the nodes on the water surface layer forward the data to the nearest sink node on the water surface;

the cluster nodes are mutually cooperated and communicated, and the collected data is forwarded to the corresponding cluster head node, and the method comprises the following steps: the nodes participating in the communication are set as follows: a source node, a relay node and a destination node;

the source node broadcasts to the relay node and the destination node at the same time, threshold value prejudgment is carried out at the destination node, and the quality of a transmission signal is judged by utilizing a noise threshold;

and if the signal quality received by the destination node is lower than the noise threshold value, starting the relay node to perform cooperative transmission of data, namely backing up and retransmitting the data packet.

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