Research On Underwater Data Collection Algorithm Based On Submersible Synergy

Underwater data collection is the foundation of underwater sensor network application research.In underwater sensor networks,the sparsity of sensor node deployment limits the range of data collection.The underwater submersible promotes the deployment of sensor networks with its flexibility and autonomy to maximize network coverage.However,although the autonomy of underwater sensor network can be improved by deploying submersible,the cost of submersible limits its large-scale deployment.In view of the above challenges,a small number of submersible devices are deployed on the basis of sensor network,and an underwater data collection algorithm based on submersible collaboration is designed.The main research work of this paper is as follows:1.Aiming at the energy balance problem of sensor network,an underwater data collection algorithm based on single submersible collaboration is proposed.In order to ensure energy consumption equalization and connectivity,a sensor node topology optimization scheme based on rigid graph is first proposed,and the energy optimization problem is given to minimize the sum of weights;sensor nodes make routing decisions to fuse the collected data into the data collector.Then the underwater submersible dynamically selects the next data collector to access according to the data value.The feasibility of the scheme is verified by simulation results.2.Aiming at the complexity of underwater environment and the mobility of sensor nodes,a single submersible cooperative forwarding and moving underwater data collection algorithm is proposed.In order to reduce the influence of node movement,a topology optimization scheme based on minimum rigid graph algebraic characteristics is first proposed and energy optimization problem is combined to improve network energy balance;based on the optimized network topology,a local routing decision algorithm based on Q learning is proposed,which uses the interaction with the environment to ensure that the data collected by the sensor is transferred to the data collector successfully;a submersible path planning strategy based on Q learning is then designed so that the submersible avoids the impact of environmental barriers when accessing the sensor.Simulation and performance analysis verify the feasibility of the algorithm.3.Aiming at the problem of narrow monitoring range and long delay time of single submersible,a multi-submersible cooperative forwarding and moving underwater data collection algorithm is proposed.Firstly,a topology optimization algorithm based on minimum rigid graph is proposed to reduce sensor data delay and energy consumption by minimizing communication path;considering the influence of environmental obstacle,a local routing decision algorithm based on Q learning is designed,and the residual energy of sensor is combined to ensure the balance of network energy consumption.Then an improved contract network algorithm considering data value is proposed to reduce data delay and balance the load of submersible.The feasibility of the scheme is verified by simulation results.