Title: Path management strategy to reduce flooding of grid fisheye state routing protocol in mobile ad hoc network using fuzzy and rough set theory

Authors: Nithya Rekha Sivakumar; Abdullah Alaraj

Addresses: Computer Science Department, College of Computer of Science, Princess Nourah Bint Abdulrahman University, Riyadh, Kingdom of Saudi Arabia ' IT Department, College of Computer, Qassim University, Buraydah, Kingdom of Saudi Arabia

Abstract: In ad hoc mobile wireless networks, energy consumption is an important issue as most mobile hosts operate on limited battery resources. Most of the existing ad hoc routing algorithms select the shortest path using various resources (energy). Approach: to overcome these problems an optimal path management approach called path vector calculation based on fuzzy and rough set theory were addressed. The ultimate intent of this study is to select the qualified path based on energy consumption of the node in the network. Simple rules were generated using fuzzy and rough set techniques for calculating path vector and to remove irrelevant attributes (resources) for evaluating the best routing. The set of rules were evaluated with proactive protocols namely fisheye state routing (FSR) protocol in the NS-2 simulation environment based on metrics such as total energy consumed, average energy consumed, overall residual energy and average residual energy and it also considers the importance of the objects (nodes). The results have shown that in MANET, decision rules with fuzzy and rough set technique has provided qualified path based best routing. The network life time and performance of proactive protocols in MANET has improved with fuzzy and rough set based decision rules.

Keywords: fuzzy cost; fuzzy and rough set theory; path vector; membership function information gain; energy consumption; grid fisheye state routing; GFSR protocol.

DOI: 10.1504/IJAISC.2017.088883

International Journal of Artificial Intelligence and Soft Computing, 2017 Vol.6 No.3, pp.187 - 208

Received: 13 Mar 2017
Accepted: 11 May 2017
Published online: 22 Dec 2017 *

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