ENERGY EFFICIENT CLUSTERING ALGORITHM AND DATA AGGREGATION WIRELESS SENSOR NETWORKS

Abstract

Wireless sensor networks (WSNs) are used in various application such as tracking, monitoring etc. Though WSNs have great potential and are employed in variety of environments, they come with some limitations as the sensor nodes used in WSNs have limited processing capability, low battery power, low bandwidth for communication and less memory space. WSNs contain battery powered nodes where replacement of nodes is impractical. Routing protocols in WSNs aim to maximize the life time of network and energy used by the sensor nodes. Lots of work has been done on how to increase the energy efficiency of the WSNs. Clustering techniques are used to enhance the life time of network. It reduces the transmission cost and redundancy of data. Sensor nodes send the data to their cluster heads. Cluster heads aggregate the data and send it to the base station. Clustering also enhances the stability period of network which is the time period till all the nodes are alive in the network. Various data aggregation techniques have been proposed to improve the network life time. Thus clustering and data aggregation are important techniques to enhance the network life time. In this dissertation we improve the performance of energy efficient sleep awake and aware protocol on the basis of (1) Cluster head selection (2) Optimal no. of Cluster Heads (CHs) and (3) Multi hop strategy. In this thesis we consider heterogeneous networks to evaluate the performance of proposed energy efficient clustering and data aggregation technique. Our goal is to minimize the energy consumption and extend the life time and stability of network. Simulation results are shown for the performance analysis of the proposed energy efficient clustering algorithm and data aggregation (EECAA).