A Study On Cluster Head Selection Scheme For LEACH-C In Wireless Sensor Network

Wireless sensor network, which has functions of information collection, information processing and information transmission, is a new network system. With the development of related technologies, wireless sensor network is more and more used in many areas, such as environmental monitoring, battlefield investigation, public safety, smart home and so on. Because of nodes having limited energy and limited computing and storage capacity, how to improve energy efficiency and extend the lifetime is a vital issue in research of wireless sensor network. An effective method to prolong the network lifetime is to design an energy efficient routing protocol.This thesis introduces plane and layer routing protocols of wireless sensor network. In order to compare advantages and disadvantages of various protocols, this thesis selects four protocols, which are Minimum Transmission Energy(MTE), Static-clustering, Low-Energy Adaptive Clustering Hierarchy(LEACH), Low-Energy Adaptive Clustering Hierarchy-Central(LEACH-C), to analysis the number of alive nodes, energy consumption and the amount of data received in base station. Simulation results show that dynamic clustering routing protocols perform better than static clustering routing protocols and plane routing protocols.This thesis proposes an improved scheme of cluster head selection based on node residual energy for the lack of cluster head selection in LEACH-C. This scheme determines range of nodes that can participate into cluster head selection based on energy consumption of each round. It increases probability of nodes that have higher residual energy to be cluster head so that it can balance energy distribution and extend lifetime of the network. A comparison among LEACH, LEACH-C and the proposed algorithm on the death time of the first node by NS2 software are made to verify the validity of proposed algorithm. Simulation results show that the proposed algorithm can prolong the time of first node death and lifetime of the network. Finally, in order to prove the correctness of analysis, this thesis calculates variance of residual energy to assess the energy distribution. Simulation results show that the proposed algorithm can effectively reduce the residual energy variance, balanced energy distribution and improve energy efficiency before first node death.