Research On Wireless Sensor Network Coverage And Resource Optimization

Wireless sensor networks consist of a large number of sensor nodes with sensing,computing and communication capabilities.Nodes have miniature,inexpensive,and low-power embedded systems that coordinate with each other to form a multi-hop and self-organizing network.Wireless sensor networks are characterized by distributed and self-organization,dynamic topology,sensor node resource constraints,node computing,storage,communication capability constraints,large scale distribution,data center and multi-hop routing.This kind of emerging cross-type information capture technology is widely used in national defense and military,medical and health,environmental monitoring,natural disaster,agricultural equipment,traffic management,smart home and many other fields.Therefore,wireless sensor networks have attracted attention and exploration from the business community and academia.Considering the limited radius of the node sensing radius and the complexity of the deployment condition,there are some problems such as inefficient information capture and large energy consumption in the monitoring process.Therefore,how to improve the wireless sensor network coverage and network life has become a key research topic.This topic is based on two aspects of the coverage problem and the resource problem to carry on the optimization research to the wireless sensor network.The main innovation of this paper includes the following aspects:1.Research on coverage optimization of wireless sensor network for deterministic deployment.A wireless sensor network coverage optimization based on improved particle swarm optimization is proposed to settle the trouble of wireless sensor node deterministic disposition.Regional coverage is seen as an optimization goal,combined with the standard particle swarm optimization algorithm,and the deployment location of all nodes is optimized to enhance the area coverage.The experimental results demonstrate that the influence of different perceived radius on the optimization performance of the network coverage and the optimization performance comparison graph of the standard particle swarm,chaos particle group and cross particle swarm optimization,and prove that the latter two algorithms solve the network coverage better than the first algorithm.2.Research on periodic dispatching system of wireless sensor networks for random deployment.Taking the large-scale sensor nodes or the extremely complex regional environment into account,the staff is difficult to enter the monitoring area to replace the node of the battery and to precisely adjust the node location.The more practical measure is nodes are randomly sprinkled in the designated monitoring area.A wireless sensor network coverage periodic scheduling optimization scheme based on genetic algorithm is proposed for wireless sensor node scheduling problem of random deployment.By analyzing the energy capture problem of wireless sensor network random deployment,the problem of periodic scheduling optimization in synchronous and asynchronous network environment is studied respectively.And the traditional genetic algorithm and multi-population genetic algorithm are used to obtain the optimal periodic scheduling scheme and the optimization performance comparison graph of the corresponding algorithm.Simulation experiments and analysis show that the scheme not only guarantees the event capture rate,but also achieves the energy efficient capture.3.Research on cross-layer optimization of lifetime and utility in wireless sensor networks.Aiming at the limited energy of wireless sensor networks,an optimization model for cross-media access layer and traffic transmission layer is proposed.Construct a mathematical optimization model based on the goal of improving the life and utility of the wireless sensor network,satisfying the link transmission capacity and guaranteeing the life of the wireless sensor network.Firstly,the weighted method is adopted to convert the dual goals into single-objective optimization.The Lagrange vertical decomposition method divides the original problem into two single-layer optimization problems: the media access control layer and the traffic transmission control layer.Then,the updated formula of the Lagrangian multiplier and the link transmission probability are deduced,according to the gradient projection method.Finally,an optimized solution is obtained.The experimental results prove that the scheme improves both the application utility and the lifetime of the wireless sensor network based on the support of network target lifetime and link transmission capacity.