Lifetime Enhancement of Wireless Sensor Networks Using Optimised Clustering and Routing Techniques

Abstract

Though a lot of research has been carried out in the area of Wireless Sensor Networks (WSN), still there are lot of challenges and gaps in this field. Issues related to energy, security and data transmission methods have been explored during the last two decades; yet a few issues such as maximizing the network lifetime in WSN need a deeper analysis. It is known that once the nodes have been deployed, recharging is not possible. So, it is necessary to increase the lifespan of networks by using different energy management techniques. newlineIt is known that clustering is one of the popular methods for conserving energy in WSNs. Various factors such as nodes nearer the sink requiring greater energy, selection of cluster heads and proper distribution of energy to nodes are still posing great challenges to designers in clustering. newlineSimilarly, the task of identifying the optimal routes for transmission of data is also essential. Selection of paths with minimum distance between source and destination, use of multihop paths, selection of relay nodes which have maximum energy etc. also help in reducing the energy consumption which results in enhancement of network lifetime substantially. newlineWireless sensor networks are required to be deployed in hostile fields, unmanned areas, difficult terrains, areas without infrastructure support and harsh environments, for the purpose of monitoring atmospheric parameters, for detecting enemy movements in battle fields, for precision farming etc. It is therefore pertinent that nodes should be deployed in such a way that maximum area should be covered with minimum count of nodes ensuring that all the targets are covered. newlineIssues related to clustering and routing of WSN are addressed in this research. Techniques that are based on appropriate clustering, cluster head selection and strategic routing are explored for this purpose. newlineTwo conventional hybrid techniques and three novel Bio inspired techniques are proposed in this thesis.Clustering and Routing are implemented using these techniques. newline