Congestion-aware and Predictive Geo-Casting Routing Mechanisms for Mobile ad hoc Network

Abstract

Mobile Ad-hoc Networks (MANETs) has gained remarkable appreciation during the last decade because of its high flexibility. Due to high mobility and unpredictable topology changes, most of the existing routing protocols are unable to adapt to these changes and efficient route selection becomes a challenging task. The existing routing protocols incur high control overhead during route discovery process, tendency to select an unreliable route and high data packet loss during route maintenance. Therefore, this paper presents A Congestion-aware and Predictive Geo-casting Routing Mechanism (CPGR) for MANET that optimally utilize the constrained network resources and reliably detect high-quality links. CPGR exploits a multi-facet routing strategy that takes into consideration the congestion level, relatively higher signal strength, and hop-counts of neigh- boring nodes while making routing decisions. This strategy not only ensures data dissemination via high quality nodes but also balances out resource consumption among nodes while traversing through shorter paths. Demonstrated by simulation results in NS-2, CPGR achieves improved performance in terms of end-to-end delay, control overhead, and packet delivery ratio as compared to existing solutions.