Improved Fair-Zone technique using Mobility Prediction in WSN

The self-organizational ability of ad-hoc Wireless Sensor Networks (WSNs) has led them to be the most popular choice in ubiquitous computing. Clustering sensor nodes organizing them hierarchically have proven to be an effective method to provide better data aggregation and scalability for the sensor network while conserving limited energy. It has some limitation in energy and mobility of nodes. In this paper we propose a mobility prediction technique which tries overcoming above mentioned problems and improves the life time of the network. The technique used here is Exponential Moving Average for online updates of nodal contact probability in cluster based network.Comment: 10 pages, 7 figures, Published in International Journal Of Advanced Smart Sensor Network Systems (IJASSN

CLUSTERING BASED ROUTING FOR DELAY- TOLERANT NETWORKS

ABSTRACT Delay-tolerant networking (DTN) is an approach to computer network Clustering significantly reduces the energy consumption of a cluster. In this paper, a cluster based routing protocol for Delay-Tolerant Mobile Networks (DTMNs) is used. Exponentially weighted moving average (EWMA) scheme is employed for on-line updating region contact probability, with its mean proven to converge to the true contact probability. The gateway nodes exchange network information and perform routing. It uses clustering's structure to decrease overhead, average end-to-end delay and improve the average packet delivery ratio