HAC: Hierarchical Agglomerative Clustering With Linear Programming for Wireless Sensor Networks

Abstract

Wireless sensor networks are a collection of tiny sensor devices powered by energy-scarce batteries. Depending on the nature of the application, those tiny devices might be deployed in areas that make it difficult to recharge or change their battery. Therefore, it is important to optimize the energy consumption of these devices to prolong their lifetime for as long as possible. Clustering is regarded as the most efficient approach to extend the lifetime of wireless sensor networks. This study proposes a novel method integrating cluster head selection and cluster formation to obtain as long a network lifetime as is possible. We employ a linear programming model to resolve the issue of cluster head selection and a Hierarchical Agglomerative Clustering (HAC) method to form clusters in the network. We evaluated HAC on different sets of inputs where we varied the position of the sink from the corner of the network to the center. HAC outperformed other existing clustering techniques for the first node death (FND) and half node death (HND) lifetime definitions in the cases where the sink is at the corner of the network. In the cases where the sink is located at the center of the network, HAC outperformed the other existing techniques for all definitions of network lifetime.INDEX TERMS Clustering, linear programming, network lifetime, power optimization, wireless sensor network.