A regression-based technique for link failure time prediction in MANET

Abstract

Mobile ad-hoc network (MANET) is a collection of mobile terminals forming an infrastructure-less and quickly deployable network, in which nodes can communicate to each other via multiple hops. Mobility attribute is a notable one in MANET, as this leads to frequent topology changes, so this is the primary cause of link failure. Link failure time estimation has always remained an active area of research among researchers of the networking community. This paper explores various link failure time prediction techniques and proposes a novel least-squares polynomial regression-based statistical technique to estimate the link failure time in MANET. Each node in the network periodically broadcasts hello packets to register its presence with neighbouring nodes. A neighbour node receives these packets and uses its signal strength to estimate the link failure time with help of quadratic least-squares regression. The outlined technique is simulated using Network Simulator 2.35. The performance of the estimation accuracy of the suggested technique and existing interpolation-based technique has been examined for numerous mobility and scalability scenarios.