Bandwidth estimation in high mobility scenarios of MANET using NSGA-II optimized fuzzy inference system

Abstract

Integration of mobility to sensor node enhanced the scalability of Ad-hoc networks. Bandwidth estimation in scenarios where nodes move randomly and frequently changes its link may depend on factors other than congestion in network traffic. The event of link failure due to the high mobility behavior of nodes in the path from source to destination is one of the dominating cause. However, in both cases, TCP’s new-Reno and its variants reduce the congestion-window size to half or 1-MSS, which can cause bandwidth underutilization in the event of a packet drop due to link failure. The proposed approach distinguishes the link failure from network congestion and estimates bandwidth based on link and path stability matrix. The contribution includes the identification of node mobility fuzziness in unicast and broadcast scenarios of IEEE 802.15.4 based MANET. The mobility-fuzziness formulation by the proposed NSGA-II optimized fuzzy-inference-system imitates the node’s mobility behavior and, in the event of packet loss, is employed to realize the path-stability metric to estimate the congestion window size. The thorough evaluation with current state-of-the-art techniques shows that the proposed path stability metric allows the estimation of congestion window size to the current congestion window in the event of a packet loss due to link failure. Improving the bandwidth utilization metric in high mobility scenarios from 53–61% for existing approaches to above 83% in proposed approach.