%0 Journal Article
%T Comparison of Residual Energy-Based Clustering Algorithms for Wireless Sensor Network
%A Asis Kumar Tripathy
%A Suchismita Chinara
%J ISRN Sensor Networks
%D 2012
%R 10.5402/2012/375026
%X Wireless sensor network swears an exceptional fine-grained interface between the virtual and physical worlds. The clustering algorithm is a kind of key technique used to reduce energy consumption. Many clustering, power management, and data dissemination protocols have been specifically designed for wireless sensor network (WSN) where energy awareness is an essential design issue. Each clustering algorithm is composed of three phases cluster head (CH) selection, the setup phase, and steady state phase. The hot point in these algorithms is the cluster head selection. The focus, however, has been given to the residual energy-based clustering protocols which might differ depending on the application and network architecture. In this paper, a survey of the state-of-the-art clustering techniques in WSNs has been compared to find the merits and demerits among themselves. It has been assumed that the sensor nodes are randomly distributed and are not mobile, the coordinates of the base station (BS) and the dimensions of the sensor field are known. 1. Introduction With the proliferation in automated devices and the development in wireless technologies WSNs have gained worldwide attention in recent years. WSNs as an exciting emerging domain of deeply networked systems of low-power wireless nodes with a tiny amount of CPU and memory for high-resolution sensing of the environment [1]. The wireless nodes are nothing but a large number of low-cost, multifunctional sensor nodes that are deployed in a region of interest. The sensor nodes not only senses but also processes the data to make itself meaningful by using its embedded microprocessors and also communicates those meaningful data through its transceiver [2]. They communicate over a short distance via a wireless medium and collaborate to accomplish a common task, for example, environment monitoring, battlefield surveillance, and industrial process control [3]. WSNs are made up of a large number of inexpensive devices that are networked via low-power wireless communications [4, 5]. Due to the networking capability that fundamentally appears in a sensor network, it overcomes the flaws present in a mere collection of sensors, by enabling cooperation, coordination, and collaboration among sensor assets [6]. Wireless sensor network technology is expected to have a significant impact on our lives in the twenty-first century by harvesting advancements in the past decade in microelectronics, sensing, analog and digital signal processing, wireless communications, and networking. Wireless sensor networks differ
%U http://www.hindawi.com/journals/isrn.sensor.networks/2012/375026/