Research On Coverage Control Strategy And Algorithm For Underwater Wireless Sensors Networks

Underwater wireless sensor networks(UWSNs)are network-monitoring systems consisting of sensor nodes with the capabilities of computing in an underwater environment in a self-organized manner.UWSNs can be applied to underwater information or resources collection and detection,underwater disaster forecast and military defense of the territorial sea and other fields.The research on UWSNs includes network coverage control,node location,time synchronization,underwater communication security and network energy effectiveness.Network coverage control is the first step of other researches,which has important research significance.The research on the network coverage control of underwater wireless sensor networks includes the node deployment,the network K-coverage,the network coverage preserving and holes restoration.In view of the problem of node deployment and network K-coverage,the paper conducts the following researches:For the move-restricted node self-deployment problem,the uneven cluster and radius-adjusting self-deployment algorithm(URSA)is presented.The algorithm begins the uneven clustering process according to the distance to the sink node and forms an uneven layout.And the cluster head node then forms a connected path to the Sink node to ensure network connectivity.At last,the cluster head node adjusts the its depth with the principle of maintaining the uneven network layout on the water surface,and optimize the positions of its cluster-in nodes by minimizing the hop of network.The simulation results show that the algorithm can improve network reliability,balances and reduces network energy consumption and improves the network coverage rate.For the free-to-move node self-deployment problem,the Pigeon-based Self-deployment Algorithm(PSA)is proposed.Firstly,Sink node finds the one-hop nodes and maximizes the coverage ratio of the one-hop field of Sink node;the one-hop node then layers and clusters the network,and the cluster head node forms a connected path to the Sink node to ensure network connectivity.Finally,the cluster head node regards the ratio of the node moving distance of the covering redundancy as the target and optimizes the deployed position of the node by the Pigeon Swarm Algorithm.The simulation results show that the algorithm can improve the network connectivity and network reliability,reduce the deployed energy consumption,and improve the network coverage to a certain extent.For the event K-coverage problem,the distributed and energy-efficient event K-coverage algorithm(DEEKA)is proposed.At first,nodes compete for the management node of the event by the indicator,including the number of candidate nodes,average residual energy of neighbor nodes,and distance to the event.Each management node then calculates the probability of each dynamic candidate node being selected by the corresponding event it manages.Each management node builds a multi-objective optimization model with regard to the expected energy consumption of its neighbor nodes,residual energy variance of its neighbor nodes,and the detected performance for the events it manages as targets.And finally,the management node selects the optimal scheduling policy.Simulation results show that the algorithm can better balance and reduce network energy consumption,thereby prolonging the network's best service quality and lifetime.