A Bi-directional Energy Splitable Model for Energy Optimization in Wireless Sensor Networks

A. Rajeswari (1), P.T. Kalaivaani (2)
(1) Department of Electronics and Communication Engineering, Coimbatore Institute of Technology, India
(2) Department of Electronics and Communication Engineering, Sri Krishna College of Engineering and Technology, India
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How to cite (IJASEIT) :
Rajeswari, A., and P.T. Kalaivaani. “A Bi-Directional Energy Splitable Model for Energy Optimization in Wireless Sensor Networks”. International Journal on Advanced Science, Engineering and Information Technology, vol. 1, no. 4, Aug. 2011, pp. 347-50, doi:10.18517/ijaseit.1.4.72.
Wireless Sensor Networks is a budding  prototype of networking and computing, where a node may be self powered and individual node have the capability to sense and compute and communicate. Wireless Sensor Networks have been proposed for variety of applications such as Industrial control and monitoring and home automation and consumer electronics and security andMilitary sensing, Asset tracking and supply chain management, Intelligent Agriculture, Missile directing, Fire alarming, Landslide Warning, Environmental monitoring and health monitoring and commercial applications. In Wireless Sensor Network large number of nodes are deployed randomly. Depends on the network architecture the application may be personalized such as Energy Efficiency, Routing and Power Management and data dissemination. Energy Optimization involves in minimizing an energy expenditure and maximizing the lifetime of the complete network. In the proposed work, the placement of nodes are directly involved with residual energy. Energy Optimization in sensor network is very difficult task to achieve it. The optimization of energy is performed through Bidirectional Energy Splitable Model. The data flow in both forward and backward directions are considered, In order to achieve the best QOS in transmission, some parameters such as load, delay and direction of individual nodes are considered. A mathematical model is developed to determine the data flow of  individual node based on the residual energy.

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