IEEE Sponsored 2nd International Conference on Innovations in Information Embedded and Communication Systems ICIIECS’15 927 Efficient clustering and Energy optimization Algorithm for WSNs: An approach in environment monitoring system Y.Chalapathi Rao Research Scholar ANU College of Engg & Tech. ANU, Guntur,AP, India. chalu.8421@gmail.com Dr Ch. Santhi Rani Professor, Dept. of ECE DMSSVH College of Engineering Machalipatnam, AP, India. Santhirani.ece@gmail.com Dr Syed Basha S Principal & Professor (ECE) AIET,Hyderabad Telangana, India shaikarchi@yahoo.com Abstract- In recent progress in Wireless Sensor Networks (WSNs) has been developing into one of the main attractive networking technologies, as it can be deployed without communication structures. A sensor network is composed of a number of sensor nodes which are responsible for regulation of the physical experience and transmission of the periodical results to the BS (base station). Consequently, minimize the energy consumption and extend the network lifetime are the key challenges in wireless networks. In this aspect, we proposed a hierarchical clustering method algorithm, PESCA (Position Energy Spectral Cluster Algorithm) that determine the number of clusters in a network automatically, depending on residual energy and BS distance. The idea of this clustering scheme is to modify the -means algorithm and proposes new features of the network nodes .In addition, we present a distance-energy cluster structure algorithm (DECSA) based on the classic clustering algorithm LEACH. The experiments results show that the proposed algorithm presents a significant performance improvement in terms of energy and efficient clustering. Keywords—Cluster Algorithm; DECSA; efficiant clustering; PESCA; power reduction. I. INTRODUCTION Integrated Digital Electronics, Micro-Electro- Mechanical System (MEMS) and Wireless Communications, has facilitated to the progress of microsensors. These sensors are small devices of multifunctional and communicate freely over short distances [2] with low power and low-cost. These sensor nodes are responsible for regulation of the physical experience and transmission of the periodical results to the BS that is sensing, processing the data, delivery the data to the BS and work together to form WSNs. In WSNs the sensor nodes are often grouped and placed in a large scale of given area as randomly or manually, sensing the data of each node is gathered to a sink as collect local physical information, process them, and send them to a BS while BS is connected to the internet shown in figure 1. In addition, significant characteristic of a WSN is the capability of its nodes to cooperate and responsible for data fusion. The sensor nodes are able to make use of their processing ability to locally carry out calculations and fusion operations to transmit required information only [5]. Figure 1: A wireless sensor network model The characteristics of WSNs facilitate them to be used in various areas especially for surveillance environment phenomena and in some cases react in response to the observed phenomena. In future, WSNs is a promising green technology for the efficiently detecting the variation of the environment compared with traditional techniques. WSNs for environment monitoring composed of a large number of low cost battery-powered sensor nodes, closely placed throughout an inaccessible physical area or space [9]. Thus, gives rise to the main challenge in the WSNs is the limited processing power resources of sensor nodes. In practice, it is difficult to replace or recharge the nodes batteries after reduction of their energy because; the nodes are deployed in adverse environments [11]. Consequently, the sensor network protocols have to focus initially on energy management to maximize the network lifetime [1] while traditional networks intend to get a high level quality of service (QoS). Many research issues are addressed in this area. However, the design of the proposed efficient clustering and energy optimization algorithm for WSNs is the most promising solution amongst them [13]. In WSNs sensor nodes are grouping efficiently into individual disjoint sets referred as a cluster. In WSNs clustering is provide, efficient utilizing of strained resources, network scalability, resource distribution and that gives