An adaptive clustering-based resource discovery scheme for large scale MANETs

Authors:
Saad Al-Ahmadi;Abdullah Al-Dhelaan
Affiliations:
Computer Science Department, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia;Computer Science Department, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia
Venue:
SITE'12 Proceedings of the 11th international conference on Telecommunications and Informatics, Proceedings of the 11th international conference on Signal Processing
Year:
2012

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Abstract

An increasing number of smart mobile devices offering the ability to perform various types of ubiquitous computation are emerging as large computer networks with an unprecedented scale. Large Scale Mobile Ad Hoc Networks (MANETs) place strong challenges on many aspects of network modeling, deployment, protocols, and resource discovery. Existing policies and techniques in MANETs need to be scaled efficiently as the average deployable network size increases. In this paper, we propose a new resource discovery scheme based on adaptive multi-hop clustering algorithm that divides the large network into several non-overlapping localities. Each cluster has members that are on average d-hops away from their clusterhead. The proposed resource discovery algorithm is a weight-based clusterhead election process that takes into consideration the dynamic topology changes of MANET due to nodes mobility and/or energy depletion. A comparative study is conducted by simulation to demonstrate the superiority of our scheme compared to other proposed techniques in the literature in terms of number of clusters, cluster size, cluster stability and nodes reaffiliation as measures to the algorithm efficiency.