IJSRD - International Journal for Scientific Research & Development| Vol. 2, Issue 07, 2014 | ISSN (online): 2321-0613 All rights reserved by www.ijsrd.com 118 Cluster Head Selection Techniques for energy efficient Wireless Sensor Network: A Survey Santokh Singh 1 Gagandeep Singh 2 1,2 Department of Computer Science Engineering 1,2 Chandigarh Engineering Colleges, Landran, India Abstract— Wireless sensor networks are widely considered as one of the most important technologies. The Wireless Sensor Network (WSN) is a wireless network consisting of ten to thousand small nodes with sensing, computing and wireless communication capabilities. They have been applied to numerous fields such as healthcare, monitoring system, military, and so forth. Recent advances in wireless sensor networks have led to many new protocols specifically designed for sensor networks where energy awareness is an essential consideration. Energy efficiency is thus a primary issue in maintaining the network. Innovative techniques that improve energy efficiency to prolong the network lifetime are highly required. Clustering is an effective topology control approach in wireless sensor networks. This paper elaborates several techniques like LEACH, HEED, LEACH- B, PEACH, EEUC of cluster head selection for energy efficient in wireless sensor networks. Key words: Wireless sensor networks, Cluster head I. INTRODUCTION Recent advances in micro-electro-mechanical systems (MEMS) technology, wireless communications, and digital electronics have enabled the development of low-cost, low- power, multifunctional sensor nodes that are small in size and communicate untethered in short distances. These tiny sensor nodes, which consist of sensing, data processing, and communicating components, leverage the idea of sensor networks based on collaborative effort of a large number of nodes [1]. Such sensors are generally equipped with data processing and communication capabilities. The sensing circuitry measures ambient conditions related to the environment surrounding the sensor and transform them into an electric signal. Processing such a signal reveals some properties about objects located and/or events happening in the vicinity of the sensor. The sensor sends such collected data, usually via radio transmitter, to a command center (sink) either directly or through a data concentration center (a gateway) [3]. WSN is a network of tiny battery powered sensor nodes of limited on-board processing, storage and radio capability. Sensor nodes are usually deployed in a random fashion, and collect the context information and perform the given mission through the cooperation with other nodes. Each sensor node transmits the sensed data to other sensor nodes or Base Station (BS). Here direct communication to the BS is impractical if the number of sensor nodes is large as a few hundreds or thousands [2]. In order to achieve high energy efficiency and increase the network scalability, sensor nodes can be organized into clusters. The high density of the network may lead to multiple adjacent sensors generating redundant sensed data, thus data aggregation can be used to eliminate the data redundancy and reduce the communication load. In periodical data gathering applications, both methods promise to efficiently organize the network since data collection and processing can be done “in place” [4]. There are three methods that can be considered as possible networking protocols: direct communication, multi- hop routing, and clustering. As direct communication between the base and a large number of sensors is extremely energy consuming, and the multi-hop routine is considered as globally inefficient, clustering seems to be the appropriate method to use, In order to send information from very high number of sensor nodes to the base station, It is necessary and economical to group sensors into clusters. Each cluster will contain a cluster head. Each cluster head gathers and sends data, from its group of sensors, to the base station. Parameters for variation of energy consumption in the nodes, there are three main problems: How many sensors should be connected to each cluster head, how many clusters is needed, and where should each cluster head be positioned. The clusters of sensors must be nonoverlapping [5]. Hierarchical clustering mechanisms are especially effective in increasing network scalability and reducing data latency, and have been extensively exploited. [7] I. LITERATURE SURVEY Geon Yong Park (et al) 2013 proposes an efficient cluster head selection method using K-means algorithm to maximize the energy efficiency of wireless sensor network. Wireless sensor network consists of hundreds to thousands of sensor nodes gathering various data including temperature, sound, location, etc. It is usually difficult to recharge or replace the sensor nodes which have limited battery capacity. In this paper idea of discovering the cluster head minimizing the sum of Euclidean distances between the head and member nodes. Experimental results shows better performance compared to classical algorithms like LEACH and HEED and planned to minimize the clustering time [2]. Kemal Akkaya (et al) 2003 shows recent routing protocols for sensor networks and presents a classification for the various approaches pursued The three main categories discussed are: data-centric, hierarchical and location-based [3]. Seema Bandyopadhyay (et al) 2003 propose a distributed, randomized clustering algorithm to organize the sensors in a wireless sensor network into clusters also integrate the algorithm to generate a hierarchy of cluster heads and examine that the energy savings increase with the number of levels in the hierarchy. By using wireless sensor network the communication or message passing process must be designed to conserve the limited energy resources of the sensors. Clustering sensors into groups, so that sensors communicate information only to cluster heads and then the cluster heads communicate the aggregated information to the processing center, may save energy. And planned to consider an underlying medium access protocol