Abstract:
Wireless sensor networks are the networks that contain many sensors which have di erent type of abilities such as sensing, communicating or processing. In recent years there are many applications based on these kind of networks. Since most of the applications in wireless sensor networks require energy consumption, the energy level of any single node becomes important. There are di erent methods in literature which provides e cient energy consumption for wireless sensor networks. Wireless network clustering is one of the major methods which has been used in many applications for energy optimization. As there are many nodes in the networks it is aimed to provide an adaptive energy consumption with clustering methods. LEACH is one of the most popular algorithm for clustering which is based on random clustering method. In this algorithm there are two di erent type of nodes as cluster heads and cluster members. Communication is provided via these cluster heads. Therefore LEACH algorithm reaches its main purpose by providing dynamic clustering and adaptive energy consumption. The main clustering algorithms are analyzed and drawbacks of the LEACH algorithm are determined in this thesis. New clustering algorithms are provided in order to prevent undesired cases of LEACH clustering algorithm. It is shown in this thesis that random methods are bene cial in clustering but not adequate enough to reach the desired results. Improving the random algorithms with di erent constraints and methods reaches better results in case of energy consumption.
