Cluster Based Algorithm for Energy Conservation and Lifetime Maximization in Wireless Sensor Networks

One of the most critical issues in designing Wireless Sensor Network (WSN) is to minimize the energy consumption. In Wireless Sensor Networks, data aggregation reduces the redundancy among sensed data and optimal sensor routing algorithm provides strategy for data gathering with minimum energy. The energy consumption is reduced by combining data fusion and cluster based routing. In this paper, we propose a K-means Fusion Steiner Tree (KFST) for energy efficient data gathering in sensor networks, which optimizes data transmission cost and the data fusion cost. This cost reduction increases the lifetime of a Sensor Network. The result of the proposed protocol KFST is compared with Adaptive Fusion Steiner Tree (AFST) and KFST produces better result than the existing protocols

Intelligent Sensor Networks

In the last decade, wireless or wired sensor networks have attracted much attention. However, most designs target general sensor network issues including protocol stack (routing, MAC, etc.) and security issues. This book focuses on the close integration of sensing, networking, and smart signal processing via machine learning. Based on their world-class research, the authors present the fundamentals of intelligent sensor networks. They cover sensing and sampling, distributed signal processing, and intelligent signal learning. In addition, they present cutting-edge research results from leading experts