CN115278633B - Maritime search and rescue wireless sensor network communication method, device and storage medium - Google Patents
Maritime search and rescue wireless sensor network communication method, device and storage medium Download PDFInfo
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Abstract
The invention relates to a maritime search and rescue wireless sensor network communication method, a device and a storage medium based on an opportunistic routing algorithm, wherein the method comprises the following steps: constructing a maritime search and rescue wireless sensor network topological structure; determining a link connectivity metric value and updating the link connectivity metric value in real time based on an update period; determining the optimal expected data packet advancing distance based on the area of the area where the relay candidate node is located; establishing a node residual energy probability distribution model; determining the priority of the relay candidate nodes based on the link connectivity metric value, the optimal expected data packet advancing distance, the distance between the relay candidate nodes and Sink nodes and the node residual energy probability distribution model, and sequencing the relay candidate nodes from high to low based on the priority; based on priority ordering, a scheduling algorithm based on a timer is adopted to coordinate the starting state of each relay candidate node, and the maritime search and rescue data packet forwarding is completed. Compared with the prior art, the invention has the advantages of high transmission rate, low time delay and the like.
Description
Technical Field
The invention relates to the field of maritime search and rescue wireless sensor network communication, in particular to a maritime search and rescue wireless sensor network communication method and device based on an opportunistic routing algorithm and a storage medium.
Background
After the marine perils happen, the existing rescue means mainly rely on search and rescue equipment such as search and rescue ships, maritime helicopters, intelligent unmanned aerial vehicles, remote radars and satellites to search and rescue. However, marine accidents mostly occur under severe sea conditions, and the rescue means have the problem that a rescue target cannot be timely and accurately searched. As one of the emerging technologies in the maritime search and rescue field, a maritime search and rescue wireless sensor network (MARITIME SEARCH AND Rescue Wireless Sensor Networks, MSR-WSNs) can timely acquire related information such as environmental parameters, node position coordinates and vital signs of people falling into water in a search and rescue sea area by utilizing information interaction among nodes, and send the related search and rescue information to Sink nodes (Sink nodes) in a multi-hop transmission mode through a node ad hoc network. The Sink node relays and transmits the search and rescue information to the maritime search and rescue command center through the maritime satellite or the Beidou satellite, so that the condition that the search and rescue target can only wait for searching passively is changed, the active position indication of the search and rescue target is realized, and the search and rescue efficiency of the maritime search and rescue command center and the rescue success rate of people falling into water are improved to a great extent.
In the maritime search and rescue process, the MSR-WSNs need to timely and accurately transmit perceived information to Sink nodes, so that the MSR-WSNs routing algorithm is required to ensure real-time and reliable data transmission. Real-time and reliable routing requires a higher connectivity and less congestion of the data transmission path. Due to the complex and changeable marine environment and the inherent dynamic characteristics and the wave shielding effect, the MSR-WSNs are difficult to realize low-time-delay efficient transmission. For MSR-WSNs, existing routing protocols suffer from the following drawbacks: 1) The calculation complexity is high, so that the data transmission delay is large; 2) The energy consumption required by route maintenance is high in a real-time dynamic environment; 3) The scenario where all nodes move in real time is not considered. Thus, existing routing protocols are not suitable for MSR-WSNs information transfer that is topologically highly dynamic and communication environment harsh. The maritime search and rescue is different from the application field of the land wireless sensor network, and is specifically expressed as follows: 1) The network topology has high dynamic property due to the real-time movement of the ocean sensor network nodes; 2) Due to the influence of wave shielding effect, the communication quality of the marine wireless channel is poor, and the conventional routing algorithm cannot meet the requirements of reliability and instantaneity of marine data transmission; 3) Ocean node batteries are typically not rechargeable and replaceable and therefore have limited energy. The robustness and the intelligence of the routing protocol of the maritime search and rescue wireless sensor network can be directly or indirectly affected by the characteristics, so that the problem of low search and rescue efficiency is faced. Therefore, a new routing method is needed to better adapt to the complex dynamic maritime search and rescue environment.
Unlike conventional routing algorithms, opportunistic routing can significantly reduce packet retransmission due to link failure by dynamically selecting a relay forwarding node from among a plurality of candidate receiving nodes. The next-hop node for packet forwarding depends on whether the candidate forwarding node receives a packet and its forwarding priority ordering. Thus, opportunistic routing can better accommodate unstable, dynamic networks. In addition, in a dynamic environment, the opportunistic routing can effectively improve the data transmission rate under the condition of poor communication channel quality, so that the method is suitable for maritime search and rescue scenes. However, opportunistic routing faces two major challenges in MSR-WSNs: 1) The problem of data packet duplication under time-varying topology; 2) The problem of determining the waiting time of a transmitting node under uncertain sea conditions. At the same time, updating the routing metrics between maritime search and rescue nodes in real time would result in higher communication costs. Therefore, a new opportunistic routing algorithm needs to be proposed to realize low-delay efficient stable transmission of maritime search and rescue data.
Disclosure of Invention
The invention aims to provide a maritime search and rescue wireless sensor network communication method, device and storage medium based on an opportunistic routing algorithm, and low-time-delay efficient stable transmission of maritime search and rescue data is realized.
The aim of the invention can be achieved by the following technical scheme:
a maritime search and rescue wireless sensor network communication method based on an opportunistic routing algorithm comprises the following steps:
Constructing a maritime search and rescue wireless sensor network topological structure;
Determining a link connectivity metric value based on a maritime search and rescue wireless sensor network topological structure and received signal strength, and updating the link connectivity metric value in real time based on an updating period, wherein the updating period is determined based on a communication radius, a maximum moving speed and a random moving model of a node;
Determining the optimal expected data packet advancing distance based on the area of the area where the relay candidate node is located;
establishing a node residual energy probability distribution model based on the energy regularization random variable;
Determining the priority of the relay candidate nodes based on the link connectivity metric value, the optimal expected data packet advancing distance, the distance between the relay candidate nodes and Sink nodes and the node residual energy probability distribution model, and sequencing the relay candidate nodes from high to low based on the priority;
Based on priority ordering, a scheduling algorithm based on a timer is adopted to coordinate the starting state of each relay candidate node, and the maritime search and rescue data packet forwarding is completed.
The link connectivity metric value is determined based on the maritime search and rescue wireless sensor network topological structure and the received signal strength, and comprises the following steps:
According to the wireless signal loss propagation model, determining the received signal strength P r (d) of the node i:
Where d is the distance from the node sending the information to the node i, P t is the transmission power of the node i, d 0 is the reference distance, d 0＝1m,PL(d0) is the signal strength loss value when the reference distance is d 0, α is the path loss attenuation index, X σ is the sea wave shielding factor, and obeys the gaussian distribution expected to be 0 and the variance σ 2;
Assuming that the communication radius of the maritime search and rescue node is r and the motion of the maritime search and rescue node follows a random movement model, the average distance of two random movement nodes in a circular area with the radius of r is 0.9054r, the influence of the wave shielding effect is ignored, and the received signal strength threshold value of the successfully received data packet of the node is defined as follows:
Determining a link connectivity metric LC representing a probability of connectivity between nodes by comparing a received signal strength threshold to a received signal strength:
Wherein, For the link connectivity metric value between node i and its neighbor node j,The larger the size, the more reliable the link,Representing that the link is not connected or is about to break.
The update period is as follows: t=t min, where T is the update period,
T min denotes the minimum time for which the link between two nodes maintains communication in opposite directions when the two nodes move at the maximum speed, where v max is the maximum movement speed of the nodes, r is the communication radius of the maritime search and rescue node, and the motion of the maritime search and rescue node follows a random movement model, and the average distance between two random movement nodes in a circular area with the radius r is 0.9054r.
The step of determining the optimal expected data packet advancing distance based on the area of the area where the relay candidate node is located comprises the following steps:
At time t, defining the distance from node i to Sink node as Y i t, and defining the average relay candidate node number of node i as Wherein,For the average density of nodes in the search and rescue area,Is the area of the area where the relay candidate node is located,
Wherein θ is a data packet forward distance control parameter, and r is a communication radius of the node;
Based on The optimal expected data packet advancing distance h (Y i t) from the node i to the next-hop relay candidate node is determined as follows:
The node residual energy probability distribution model is that The energy regularization random variable isWherein,
Where γ Φ is the node energy distribution control parameter, ζ j is the remaining energy of the relay candidate node j, e 0 is the node initial energy,Is a relay candidate node set.
The priority calculation formula of the relay candidate node is as follows:
Wherein, For the priority of the relay candidate node j at time t,For the link connectivity metric value between node i and its neighbor's relay candidate node j, d j-Sink (t) is the distance from relay candidate node j to Sink node, h (Y i t) is the optimal expected packet travel distance,And (5) remaining an energy probability distribution model for the nodes.
The priority sorting is based, a scheduling algorithm based on a timer is adopted to coordinate the starting state of each relay candidate node, and the completion of the forwarding of the maritime search and rescue data packet is specifically as follows:
Coordinating the starting state of the relay candidate nodes of the node i by adopting a scheduling algorithm based on a timer, wherein the node which is started for the first time is the relay candidate node with highest priority ranking, if the relay candidate node which is started at present does not successfully forward a data packet within waiting time, the relay candidate node with next priority ranking is started and tries to forward the data packet, and so on until the maritime search and rescue data of the node i is successfully transmitted to the relay candidate node, wherein when a certain relay candidate node is in the starting state, other relay candidate nodes keep a dormant state;
and (3) taking the relay candidate node which successfully receives the maritime search and rescue data as a node i again, updating the relay candidate node of the node i and the priority order thereof, carrying out next-hop data transmission, and the like until the maritime search and rescue data acquired by the source node are successfully transmitted to the Sink node.
The waiting time is as follows:
twait＝Te+(k-1)tmin
wherein k is the priority ordering of the relay candidate nodes;
t min denotes the minimum time for which the link between two nodes remains in communication in the opposite direction, in the case where the two nodes move at maximum speed,
V max is the maximum movement speed of the node, r is the communication radius of the maritime search and rescue node, the movement of the maritime search and rescue node follows a random movement model, and the average distance between two random movement nodes in a circular area with the radius r is 0.9054r;
t e is the expected latency of node i after the first relay candidate node is enabled,
Wherein,For the probability that one or more relay candidate nodes are enabled at time t, the sleep period of node i is an exponentially distributed random variable with mean value lambda -1, N i is the average number of relay candidate nodes of node i, For the average density of nodes in the search and rescue area,Is the area of the area where the relay candidate node is located.
The maritime search and rescue wireless sensor network communication device based on the opportunistic routing algorithm comprises a memory, a processor and a program stored in the memory, wherein the processor realizes the method when executing the program.
A storage medium having stored thereon a program which when executed performs a method as described above.
Compared with the prior art, the invention has the following beneficial effects:
(1) The invention evaluates the probability of breaking a certain link through the link connectivity metric value and sets the update period to update the link connectivity metric value in real time, thereby ensuring the high reliability and the high robustness of the routing path of the maritime search and rescue wireless sensor network.
(2) The invention synthesizes four measurement indexes, namely a link connectivity measurement value, an optimal expected data packet advancing distance, a distance between a relay candidate node and a Sink node and a node residual energy probability distribution model to calculate the priority of the relay candidate node and perform descending order sequencing, and then uses a scheduling algorithm based on a timer to coordinate the forwarding of the maritime search and rescue data packet, thereby effectively avoiding the problem of data packet replication under time-varying topology, greatly improving the transmission rate of the maritime search and rescue data packet, and effectively reducing the time delay and network energy consumption from end to end.
Drawings
FIG. 1 is a flow chart of the method of the present invention;
FIG. 2 is a schematic diagram of an application scenario of the present invention;
FIG. 3 is an initial topology of a maritime search and rescue wireless sensor network according to one embodiment;
Fig. 4 is a diagram showing a comparison of the packet forwarding rate and the average end-to-end delay performance of the opportunistic routing algorithm EELLR-OR proposed in the present invention and the existing routing algorithm performed over simulation time in an embodiment, where (a) is a packet forwarding rate comparison and (b) is an average end-to-end delay comparison;
Fig. 5 is a diagram showing a comparison of an opportunistic routing algorithm EELLR-OR proposed in the present invention with an existing routing algorithm in terms of packet forwarding rate and node average energy consumption performance as the average speed of movement of the node increases in one embodiment, where (a) is a packet forwarding rate comparison and (b) is a node average energy consumption comparison;
Fig. 6 is a graph of the opportunistic routing algorithm EELLR-OR proposed by the present invention versus the existing routing algorithm in terms of packet forwarding rate and node average energy consumption performance under variable marine environmental noise variance σ 2, where (a) is a packet forwarding rate versus graph and (b) is a node average energy consumption versus graph.
Detailed Description
The invention will now be described in detail with reference to the drawings and specific examples. The present embodiment is implemented on the premise of the technical scheme of the present invention, and a detailed implementation manner and a specific operation process are given, but the protection scope of the present invention is not limited to the following examples.
A maritime search and rescue wireless sensor network communication method based on an opportunistic routing algorithm is shown in fig. 1, and comprises the following steps:
Step 1) constructing a maritime search and rescue wireless sensor network topological structure, as shown in fig. 3.
And 2) determining a link connectivity metric value based on a maritime search and rescue wireless sensor network topological structure and the received signal strength, and updating the link connectivity metric value in real time based on an updating period, wherein the updating period is determined based on the communication radius, the maximum moving speed and the random moving model of the node.
The maritime search and rescue nodes move in real time along with the wave current, and communication links among the nodes are frequently interrupted under the severe sea conditions, so that routing failure is caused. Therefore, step 2) proposes an efficient link quality prediction method to evaluate the probability of a certain link interruption, and set an update period to update the link connectivity metric value in real time, so as to ensure the reliability of the routing path.
According to the wireless signal loss propagation model, determining the received signal strength P r (d) of the node i:
Where d is the distance from the node sending the information to the node i, P t is the transmission power of the node i, d 0 is the reference distance, d 0＝1m,PL(d0) is the signal strength loss value when the reference distance is d 0, α is the path loss attenuation index, X σ is the sea wave shielding factor, and obeys the gaussian distribution expected to be 0 and the variance σ 2;
Assuming that the communication radius of the maritime search and rescue node is r and the motion of the maritime search and rescue node follows a random movement model, the average distance of two random movement nodes in a circular area with the radius of r is 0.9054r, the influence of the wave shielding effect is ignored, and the received signal strength threshold value of the successfully received data packet of the node is defined as follows:
The receive strength threshold P R-Th represents the lowest signal strength at which a node can receive a neighbor node message. From the above equation, P R-Th is a constant when P t, α, r are determined.
Determining a link connectivity metric LC (Link Connectivity) by comparing the received signal strength threshold to the received signal strength to represent a probability of connectivity between nodes:
Wherein, For the link connectivity metric value between node i and its neighbor node j,The larger the size, the more reliable the link,Representing that the link is not connected or is about to break.
In highly dynamic marine environments, where the network topology is time-varying, the established reliable connections between nodes can typically only be maintained for a period of time, so we have to update periodicallyValues. Considering an extreme case, where two nodes move in opposite directions at maximum speed, the minimum time for which the link between the two nodes remains connected is:
Wherein v max is the maximum movement speed of the node, r is the communication radius of the maritime search and rescue node, the movement of the maritime search and rescue node follows a random movement model, and the average distance between two random movement nodes in a circular area with the radius r is 0.9054r.
To ensure thatThe update period T is set to T min and unnecessary routing overhead is avoided.
And 3) determining the optimal expected data packet advancing distance based on the area of the area where the relay candidate node is located.
At time t, defining the distance from node i to Sink node as Y i t, and defining the average relay candidate node number of node i asWherein,For the average density of nodes in the search and rescue area,Is the area of the area where the relay candidate node is located,
Wherein θ is a data packet forward distance control parameter, and r is a communication radius of the node;
Based on The optimal expected data packet advancing distance h (Y i t) from the node i to the next-hop relay candidate node is determined as follows:
From the above equation, theoretically, the number of hops from node i to Sink node at time t is
And 4) building a node residual energy probability distribution model based on the energy regularization random variable.
In the maritime search and rescue wireless sensor network, an important index for determining the priority of the nodes is the residual energy of the nodes. However, collecting the remaining energy data of the nodes in real time creates a large communication overhead.
The node residual energy probability distribution model is thatThe energy regularization random variable isWherein,
Where γ Φ is the node energy distribution control parameter, ζ j is the remaining energy of the relay candidate node j, e 0 is the node initial energy,Is a relay candidate node set.
And 5) determining the priority of the relay candidate nodes based on the link connectivity metric value, the optimal expected data packet advancing distance, the distance between the relay candidate nodes and Sink nodes and the node residual energy probability distribution model, and sequencing the relay candidate nodes from high to low based on the priority.
The priority calculation formula of the relay candidate node is as follows:
Wherein, For the priority of the relay candidate node j at time t,For the link connectivity metric value between node i and its neighbor's relay candidate node j, d j-Sink (t) is the distance from relay candidate node j to Sink node, h (Y i t) is the optimal expected packet travel distance,And (5) remaining an energy probability distribution model for the nodes.
And 6) based on priority ordering, adopting a scheduling algorithm based on a timer to coordinate the starting state of each relay candidate node, and completing the forwarding of the maritime search and rescue data packet.
Coordinating the starting state of the relay candidate nodes of the node i by adopting a scheduling algorithm based on a timer, wherein the node which is started for the first time is the relay candidate node with highest priority ranking, if the relay candidate node which is started at present does not successfully forward a data packet within waiting time, the relay candidate node with next priority ranking is started and tries to forward the data packet, and so on until the maritime search and rescue data of the node i is successfully transmitted to the relay candidate node, wherein when a certain relay candidate node is in the starting state, other relay candidate nodes keep a dormant state;
and (3) taking the relay candidate node which successfully receives the maritime search and rescue data as a node i again, updating the relay candidate node of the node i and the priority order thereof, carrying out next-hop data transmission, and the like until the maritime search and rescue data acquired by the source node are successfully transmitted to the Sink node.
The waiting time is as follows:
twait＝Te+(k-1)tmin
wherein k is the priority ordering of the relay candidate nodes; t min is the minimum time for maintaining communication between the two links in step 2); t e is the expected latency of node i after the first relay candidate node is enabled,
Wherein,For the probability that one or more relay candidate nodes are enabled at time t, the sleep period of node i is an exponentially distributed random variable with mean value lambda -1, N i is the average number of relay candidate nodes of node i, For the average density of nodes in the search and rescue area,Is the area of the area where the relay candidate node is located.
The above functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a usb disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The implementation mode of the embodiment of the invention and the advantages thereof in the maritime search and rescue field are further described by carrying out simulation analysis on the maritime search and rescue wireless sensor network communication method based on the opportunistic routing algorithm through MATLAB R2016 b.
After the marine perils occur, 100 maritime search and rescue nodes are randomly deployed in a square search and rescue sea area with a side length of 2km at the initial moment. The movement of the sensor node is modeled by using a Gaussian Markov model, and the maximum movement speed and the minimum movement speed are respectively 20m/s and 10m/s. Fig. 3 is an initial topology of a maritime search and rescue wireless sensor network. A sensor node remote from the gateway node is selected as Sink node and it is assumed that the energy of Sink node is infinite.
In the embodiment, three routing algorithms are adopted as reference algorithms to carry out comparison analysis with the maritime search and rescue wireless sensor network communication method based on the opportunistic routing algorithm, the opportunistic routing algorithm is defined as EELLR-OR, and the reference algorithms comprise a predicted opportunistic routing protocol POR, an Ant colony optimization-based enhanced dynamic source routing algorithm E-Ant-DSR and a distributed joint optimization routing algorithm DORAHP based on a hierarchical analysis method.
The simulation parameters are shown in the following table:
| Parameters (parameters) | Value of |
| e0 | 3J |
| r | 100m |
| Simulation time | 70s |
| Channel bandwidth | 2Mbps |
| Eelec | 50nJ/bit |
| εfs | 10pJ/bit/m2 |
| εmp | 0.0013pJ/bit/m4 |
| α | 3 |
| σ2 | 30dB |
| θ | 30m |
| λ-1 | 1s |
| γΦ | 2 |
Four routing algorithms are compared from the following three aspects:
1) A data packet forwarding rate;
2) Average end-to-end delay;
3) Average energy consumption of maritime search and rescue nodes.
Fig. 4 is a diagram showing the comparison between the packet forwarding rate and the average end-to-end delay performance of the opportunistic routing algorithm EELLR-OR proposed by the present invention and the existing routing algorithm performed along with the simulation time in this embodiment. As can be seen from fig. 4 (a), EELLR-OR achieves the best performance compared to the existing routing algorithm. EELLR-OR has the advantages that: 1) On the basis of considering the real-time movement of all nodes, the connectivity of the communication links between the nodes is effectively predicted; 2) The link connectivity metric value is updated periodically, so that links with smaller metric values can be deleted to a certain extent, thereby ensuring high reliability of the maritime search and rescue data transmission path. Meanwhile, the EELLR-OR algorithm forms a plurality of communication links by using an opportunistic routing technology, so that the probability of successfully forwarding the maritime search and rescue data packet to the Sink node is effectively improved. As can be seen from fig. 4 (b), the EELLR-OR algorithm has the lowest average end-to-end delay compared to the existing routing algorithm. The EELLR-OR algorithm combines the opportunistic routing technique with the optimal expected packet travel distance, reducing the end-to-end delay to a greater extent. The latency performance of the proposed opportunistic routing algorithm EELLR-OR is improved by 39.2%, 41.9% and 55.47% compared to POR, E-Ant-DSR and DORAHP, respectively, which will improve the efficiency of the maritime search and rescue to some extent.
Fig. 5 is a diagram showing the comparison between the opportunistic routing algorithm EELLR-OR provided by the present invention and the existing routing algorithm in terms of packet forwarding rate and average node energy consumption performance as the average node movement speed increases in this embodiment. As can be seen from fig. 5, the performance of all algorithms decreases to a different extent as the speed of node movement increases. The DOPAHP algorithm ignores the mobility of the node and high computational complexity, and the formed communication link is unstable, so that a new routing path needs to be formed frequently, which greatly reduces the forwarding rate of the maritime search and rescue data packet. EELLR-OR algorithm, the nodes broadcast data and attempt to find the optimal relay node in each time slot, which increases the probability that the maritime search and rescue packet is successfully and timely forwarded. As can be seen from fig. 5 (b), the node average power consumption is minimal because EELLR-OR algorithm has lower computational complexity.
In order to demonstrate the performance of the opportunistic routing algorithm EELLR-OR presented by the present invention, the present invention uses a variable marine environmental noise variance σ 2 to simulate the change in sea state conditions (the larger the value of σ 2, the worse the sea state conditions representing the search and rescue sea areas). As can be seen from fig. 6, as the σ 2 value increases, the packet forwarding rate and the node average power consumption performance of all algorithms gradually deteriorate. Because EELLR-OR algorithm comprehensively considers the quality of the communication link, the optimal expected data packet advancing distance and the node residual energy, compared with the existing algorithm, the performance is optimal. When sigma 2 is 50dB, the data packet forwarding rate of the EELLR-OR algorithm is 72%, which basically meets the requirements of maritime search and rescue.
The foregoing describes in detail preferred embodiments of the present invention. It should be understood that numerous modifications and variations can be made in accordance with the concepts of the invention by one of ordinary skill in the art without undue burden. Therefore, all technical solutions which can be obtained by logic analysis, reasoning or limited experiments based on the prior art by a person skilled in the art according to the inventive concept shall be within the scope of protection defined by the claims.
Claims (5)
1. The marine search and rescue wireless sensor network communication method based on the opportunistic routing algorithm is characterized by comprising the following steps of:
Constructing a maritime search and rescue wireless sensor network topological structure;
Determining a link connectivity metric value based on a maritime search and rescue wireless sensor network topological structure and received signal strength, and updating the link connectivity metric value in real time based on an updating period, wherein the updating period is determined based on a communication radius, a maximum moving speed and a random moving model of a node;
Determining the optimal expected data packet advancing distance based on the area of the area where the relay candidate node is located;
establishing a node residual energy probability distribution model based on the energy regularization random variable;
Determining the priority of the relay candidate nodes based on the link connectivity metric value, the optimal expected data packet advancing distance, the distance between the relay candidate nodes and Sink nodes and the node residual energy probability distribution model, and sequencing the relay candidate nodes from high to low based on the priority;
Based on priority ordering, adopting a scheduling algorithm based on a timer to coordinate the starting state of each relay candidate node, and completing the forwarding of the maritime search and rescue data packet;
The link connectivity metric value is determined based on the maritime search and rescue wireless sensor network topological structure and the received signal strength, and comprises the following steps:
According to the wireless signal loss propagation model, determining the received signal strength P r (d) of the node i:
Where d is the distance from the node sending the information to the node i, P t is the transmission power of the node i, d 0 is the reference distance, d 0＝1m,PL(d0) is the signal strength loss value when the reference distance is d 0, α is the path loss attenuation index, X σ is the sea wave shielding factor, and obeys the gaussian distribution expected to be 0 and the variance σ 2;
Assuming that the communication radius of the maritime search and rescue node is r and the motion of the maritime search and rescue node follows a random movement model, the average distance of two random movement nodes in a circular area with the radius of r is 0.9054r, the influence of the wave shielding effect is ignored, and the received signal strength threshold value of the successfully received data packet of the node is defined as follows:
Determining a link connectivity metric LC representing a probability of connectivity between nodes by comparing a received signal strength threshold to a received signal strength:
Wherein, For the link connectivity metric value between node i and its neighbor node j,The larger the size, the more reliable the link,Representing that the link is not connected or is about to be interrupted;
The update period is as follows: t=t min, where T is the update period,
T min represents the minimum time for which the link between two nodes is kept in communication when the two nodes move in opposite directions at the maximum speed, wherein v max is the maximum movement speed of the nodes, r is the communication radius of the maritime search and rescue nodes, the movement of the maritime search and rescue nodes follows a random movement model, and the average distance between the two random movement nodes in a circular area with the radius r is 0.9054r;
the step of determining the optimal expected data packet advancing distance based on the area of the area where the relay candidate node is located comprises the following steps:
At time t, defining the distance from node i to Sink node as Y i t, and defining the average relay candidate node number of node i as Wherein,For the average density of nodes in the search and rescue area,Is the area of the area where the relay candidate node is located,
Wherein θ is a data packet forward distance control parameter, and r is a communication radius of the node;
Based on The optimal expected data packet advancing distance h (Y i t) from the node i to the next-hop relay candidate node is determined as follows:
The node residual energy probability distribution model is that The energy regularization random variable isWherein,
Where γ Φ is the node energy distribution control parameter, ζ j is the remaining energy of the relay candidate node j, e 0 is the node initial energy,Is a relay candidate node set;
The priority calculation formula of the relay candidate node is as follows:
Wherein, For the priority of the relay candidate node j at time t,For the link connectivity metric value between node i and its neighbor's relay candidate node j, d j-Sink (t) is the distance from relay candidate node j to Sink node, h (Y i t) is the optimal expected packet travel distance,And (5) remaining an energy probability distribution model for the nodes.
2. The communication method of the maritime search and rescue wireless sensor network based on the opportunistic routing algorithm according to claim 1, wherein the priority ordering is based on, the scheduling algorithm based on a timer is adopted to coordinate the starting state of each relay candidate node, and the completion of the maritime search and rescue data packet forwarding is specifically as follows:
Coordinating the starting state of the relay candidate nodes of the node i by adopting a scheduling algorithm based on a timer, wherein the node which is started for the first time is the relay candidate node with highest priority ranking, if the relay candidate node which is started at present does not successfully forward a data packet within waiting time, the relay candidate node with next priority ranking is started and tries to forward the data packet, and so on until the maritime search and rescue data of the node i is successfully transmitted to the relay candidate node, wherein when a certain relay candidate node is in the starting state, other relay candidate nodes keep a dormant state;
and (3) taking the relay candidate node which successfully receives the maritime search and rescue data as a node i again, updating the relay candidate node of the node i and the priority order thereof, carrying out next-hop data transmission, and the like until the maritime search and rescue data acquired by the source node are successfully transmitted to the Sink node.
3. The maritime search and rescue wireless sensor network communication method based on the opportunistic routing algorithm according to claim 2, wherein the waiting time is:
twait＝Te+(k-1)tmin
wherein k is the priority ordering of the relay candidate nodes;
t min denotes the minimum time for which the link between two nodes remains in communication in the opposite direction, in the case where the two nodes move at maximum speed,
V max is the maximum movement speed of the node, r is the communication radius of the maritime search and rescue node, the movement of the maritime search and rescue node follows a random movement model, and the average distance between two random movement nodes in a circular area with the radius r is 0.9054r;
t e is the expected latency of node i after the first relay candidate node is enabled,
Wherein,For the probability that one or more relay candidate nodes are enabled at time t, the sleep period of node i is an exponentially distributed random variable with mean value lambda -1, N i is the average number of relay candidate nodes of node i, For the average density of nodes in the search and rescue area,Is the area of the area where the relay candidate node is located.
4. A maritime search and rescue wireless sensor network communication device based on an opportunistic routing algorithm, comprising a memory, a processor and a program stored in the memory, wherein the processor implements the method of any one of claims 1-3 when executing the program.
5. A storage medium having a program stored thereon, wherein the program, when executed, implements the method of any of claims 1-3.
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