Research On Multi-objective Clustering And Routing Algorithm In Wireless Sensor Networks

With the continuous development of computing and sensing technologies,WSN is widely applied in various fields,such as storage management,environmental monitoring,intelligent transportation,etc.The key technologies of wireless sensor networks(such as clustering and routing protocol,network coverage and network planning,topology control and network security,etc.)have been developed rapidly and the related technology products are gradually used in more and more extensive scenarios.The application of internet of things technology promotes the development of social production and improves people's lives.However,sensor nodes in WSN have limited power,and they could not be recharged after the deployment to the working area.Hence,the construction of the energy efficient WSN clustering routing protocol and extending the life cycle of the network become the core targets in the wireless sensor networks.This paper discusses the application scenarios and main ideas of multi-objective algorithms,and analyzes the complexity of clustering and routing in wireless sensor networks.It is difficult to accurately describe the relationship between multiple objective functions by means of weighted summation.In this paper,we aim to construct the multi-objective functions of the wireless sensor networks to improve the running time of the network effectively by using the ideas of multi-objective algorithms.This paper proposes an energy efficient clustering and routing algorithm based on multi-objective algorithms.In clustering phase,this algorithm takes multiple factors into account such as nodes' energy,the distance to the cluster heads,etc.Additionally,in routing phase,it considers nodes' energy,the hops to the base station(BS)and the energy consumption variance of cluster head node,etc.Then,this paper proposes a non-uniform clustering strategy based on the residual energy and location of the cluster heads to avoid hot spot problem caused by multi-hop communication.Finally,this paper simulates the proposed algorithm and compares with some existing clustering and routing algorithms to demonstrate the advantages of the algorithm proposed in this paper.