Improved Fair-Zone technique using Mobility Prediction in WSN

TL;DR

This paper introduces a mobility prediction method using Exponential Moving Average to enhance energy efficiency and extend the lifetime of cluster-based Wireless Sensor Networks by addressing node mobility and energy limitations.

Contribution

It proposes a novel mobility prediction technique that improves network lifetime in WSNs by better managing node mobility and energy consumption.

Findings

Extended network lifetime demonstrated

Improved energy efficiency in clustering

Enhanced node contact probability estimation

Abstract

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.