Distributed Clustering Using Enhanced Hierarchical Methodology for Dense WSN Fields
International Journal of Applied Engineering Research, Volume 10, Number 6 (2015)
Posted: 27 Jan 2017 Last revised: 29 Jan 2017
Date Written: 2015
Wireless sensor network (WSN) is formed by the grouping of wireless sensor nodes, for cooperative communication, finding applicable in environmental monitoring, battlefield surveillance, military, forest fire, sensor cloud, and in many related fields. One of the peculiar features of wireless sensor network compared to the traditional wireless communication networks is the battery power, due to the fact that the batteries of the sensor nodes have restricted lifetime and are difficult to be replaced. This is why the focus is towards energy utilization, while many of the traditional wireless networks mainly focuses on the Quality of Service (QoS). A typical wireless sensor node consumes most of its energy during communication. However, energy expenditure takes place while performing sensing and data processing operations too. This work suggests the development of an enhanced hierarchical clustering technique, the Energy-efficient Hierarchical Distributed Clustering Algorithm (EHDCA). This is a well-distributed clustering mechanism and the cluster head selection is based on residual energy, communication cost and the distance to the base station. The main characteristic feature of the proposed algorithm is the CH selection is accomplished in just few steps and its hierarchical nature. Simulation results clearly show that the proposed EHDCA scheme depicts an excellent reduction in communication energy and backbone energy consumption. Also the energy efficiency in EHDCA is improved to a great extent. It is noted that the first node death and the last node death are delayed, and the overall network lifetime is prolonged in case of the proposed EHDCA mechanism.
Keywords: Wireless sensor network, distributed clustering, cluster head, base station, energy efficiency, routing efficiency, clustering efficiency, network lifetime.
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