An Energy-Efficient Cluster-Head Selection Algorithm for Wireless Sensor Networks

Abstract

Wireless sensor netwo rk has a wide range of applications in vario us fields, extending rapidly its area due to the development of technologies both in sensor and IT. However, technology of efficient battery energy utilization cannot catch up with the rapidly developing technology in releva nt fields. Therefore, energy efficiency becomes the critical factor in wireless sensor networks that requires more attention. Clustering technology is emerging as a promising method to solve efficient energy utilization problem and various cluster-head selection techniques are now under research. This paper suggests an energy efficient cluster-head selection algorithm considering the optimal number of cluster-heads and transmission energy. Our proposed scheme selects cluster-head by computing communi cation cost in probability by adopting distance between base station and n odes to assure an o ptimal number of clusters for a given wireless sensor network. With rapidly increasing amount of information produced by the Internet users along with the constant information technology development, clustering methods are gaining more importance. Clustering technology classifies a given data into significant subgroups, minimizes energy consumption, and maximizes the life span of a network by using limited resources efficiently in various fields such as data analysis, visualization, compression, and data processing. The important goal of clustering technology research is t o extend the l ife span o f a network by distributing energy consumption fairly among all nodes. Among many clustering approaches to extend the life span of a network there are two typical methods, now under research, a cluster-head selection and optimization of the number of cluster-heads or clusters. The typical head selection methods include LEACH-C (Low-Energy Adaptive Clustering Hierarchy-Centralized) (1), EACHS (Energy Adaptive Cluster-head Selection) (2), HEED (Hybrid Energy Efficient Distributed Clustering) (3). But, LEACH- C requires a big initial cost for hardware and EACHS bears a trans mission cost to acknowledge a quantity of energy, while HEED has no guarantee on the number of cluster-heads. This research suggests the energy efficient cluster-head selection technique (EECHS), an efficient header selection algorithm that takes into account the optimal number of cluster-heads and the transmission energy. E ECHS adopts distance in formation between a n ode and base station (BS) as communication cost to ensure the optimal number of clusters. A proposed cluster-head selection method operates by computing communication cost as internal information probability to save overall communication or transmission energy. The rest of this paper consists of following chapters. Chapter 2 d escribes related cluster header selection techniques and examines HEED, the basis of selection method for EECHS, in more detail. Chapter 3 explains the cluster-head selection technique of EECHS, Chapter 4 identifies performance of EECHS whose technique suggested through analysis on the test result using a simulator, and Chapter 5 deduces a conclusion.