Research And Simulations Of Energy Optimation Based LEACH Protocols For Wireless Sensor Networks

As a novel way of acquiring and processing information,wireless sensor networks(WSNs)have been an attractive research hot-spot in the communication area.And WSNs are kind of emerging next generation wireless networks possesses comprehensive foreground. But traditional routing schemes proposed for mobile ad-hoc networks often cannot be directly applied therein. It is a hottest and most difficult problem among research on sensor networks in which how to efficiently use the node'stringent energy and geographic locations to correctly and quickly build a route to some destination area for data transmitting, and at the same time to achieve longer network lifetime by reducing node's energy dissipation. In other words, research on energy-efficent routing based on nodes'geographic information, which should be applicable to wireless sensor network, is one of the most important and challengeable work for WSNs.Wireless sensor network has large amount of nodes and these sensor nodes distribute widely in the network area, each sensor node can only get local information of the network topology, that has strain for the design of the WSNs. Meanwhile, the first priority task for routing protocol design in wireless sensor network is to increase the energy efficiency of sensor nodes and prolong lifetime of the whole network because of the limited energy, communication and computation capability of sensor nodes. Some of these schemes focus on how to select a route to minimize the energy consumption for each data transmission process, and others focus on how to minimize the overall energy consumption of the entire sensor network. Undoubtedly, through a randomly selected cluster head, the presented LEACH protocol can share the relay communication services equally and ensure all nodes bear a fair burden in the energy consumption. Ultimately LEACH protocol can extend the life-time of the whole WSNs system.This thesis first summarizes the structure,features,application fields and the way to keep power effective of wireless sensor network. In terms of analyzing the current routing protocols of wireless sensor network, aiming at the disadvantage of the protocols that have high power dissipation and short lifetime, this paper proposes an energy optimized cluster head chosen algorithm EOSA(Energy Optimized Strategy Algorithm) based on LEACH protocol.In this protocol, we chose the cluster head selection algorithm and the optimal cluster number determination as two aspact to improve the LEACH protocol.The improvement on selection of cluster head:Enabling each sensor to associate its cluster head to find a path with maximum energy residue sum instead of a path with the minimum energy consumption. The threshold value T (n) is adjusted and a new cluster head selection mechanism is adopted.The improvement on the determination of optimal clusters:As we know, in LEACH protocol, the more distance the data paths have, the more energy consumption the nodes have. The number of the optimal clusters are recalculated by analysis of the power consumption of missing broadcast package in LEACH. Meanwhile, considering the distance between the cluster head and non-cluster head node, this protocol could chose a best route from the candidate path with maximum energy residue sum.This thesis has confirmed feasibility of EOSA through the simulation experiments in the NS2 simulation platform, and theoretically verified the effectiveness fitted for LEACH protocol and related application technology. Finally, we give the conclusion of our work and suggestions for future research direction of wireless sensor networks.This thesis is supported by National Natural Science Foundation of China (No: 60773211,60672137,60970064), Open Fund of the State Key Laboratory of Software Development Environment (No:SKLSDE-2009KF-2-02), New Century Excellent Talents in university (No:NCET-08-0806), Fok Ying-Tong Education Foundation for Young Teachers in Higher Education Institutions of China (No:121067), NSF of Wuhan Municipality (No:201010621207), Specialized Research Fund for the Doctoral Program of Higher Education of China (No:20060497105) and the National Science Foundation of HuBei Province under Grant No.2008CDB335.