Research On SDWSN Topology Control And Routing Algorithm

In recent years,technologies such as big data,internet of things,and wireless communication have developed rapidly.Wireless sensor network,which is a key technology for the bottom layer of the Internet of Things,has received further attention.However,due to the inherent characteristics of WSN itself and the challenges it faces,its better application and development are restricted.Taking into account the significant innovations of software-defined networks for traditional computer networks,researchers have introduced the idea of software-defined network into WSN to propose a software-defined wireless sensor networks.The software-defined wireless sensor network has better flexibility than the traditional WSN,which helps to solve the topology control and routing problems in the WSN.Several studies have proposed a variety of software-defined wireless sensor network architectures to verify its feasibility.This paper has studied the key technology topology control and routing algorithms in the existing software-defined wireless sensor network architecture.The main works are as follows:For the problem that the existing WSN coverage optimization algorithm is difficult to dynamically adjust its coverage according to the needs of practical applications and the complexity of related algorithms is high,a SDWSN k-coverage topology control algorithm based on simplicial complex theory is proposed.The SDWSN simplicial complex is built according to the deployment of sensor nodes and under the precondition of ensuring the topology structure of SDWSN unchanged,the algorithm deletes the nodes in order by homology-preserving transformation until there are no sleepable nodes.In this way,a subset of the least active sensor nodes satisfying network1-coverage is obtained.After iteration,the disjoint minimum active sensor node subsets are selected to achieve k-coverage of the target monitoring area.The simulation results show that the proposed coverage algorithm can effectively save network energy and the algorithm has higher efficiency.On the basis of achieving the target monitoring area k-coverage,in order to solve the problem of heavy network load and high energy consumption result from the large amount of information exchange in the process of clustering and routing in existing routing algorithms,an extremum disturbed particle swarm optimization basedenergy-balanced routing algorithm is proposed.The algorithm chooses the cluster heads by considering the residual energy,position and energy balance information of the nodes and uses disturbance to improve the search performance of particle swarm optimization.Then,the network is dynamically divided into clusters of unequal size using the uneven cluster theory,one round of global clustering and k-round local cluster head updating is adopted to save the energy consumption of clustering.When building the inter-cluster routing,the shortest routing tree is constructed in a centralized way according to the link energy consumption,the residual energy of nodes and the number of nodes in the cluster.Simulation results show that the proposed algorithm can significantly improve the energy efficiency of the network and extend the network lifetime.