Study of quality of service metrics for enhancing the performance of mobile adhoc networks

Abstract

Recent advances in wireless communications support the fastestgrowing newlinedemand for communications around the world. Around the world, newlinethe demands of mobile users are increasing day by day, requiring rapid and newlineinfrastructure-less implementation of mobile connectivity. The network with newlinefrequent topology changes, self-managing, and without infrastructure is called newlinethe Mobile Ad hoc Network (MANET). It is a type of wireless network in newlinewhich the node in the network changes its location and connectivity newlinefrequently. A mobile ad hoc network requires Quality of Service (QoS) to newlineserve various applications, like wildlife monitoring, disasters, vehicular ad newlinehoc network, health monitoring, and so on. newlineDeploying QoS in MANET is hard due to frequent node position newlinechanges, topology changes, and insufficient battery power of mobile devices. newlineAnother important factor affecting QoS is node power depletion. The power newlinedepletion causes the node quickly withdraw from the network and make newlinechanges to network connectivity. Frequent network connectivity disturbance newlineadversely affects the routing of packets between the source and the intended newlinedestination. Routes between the intended nodes are important in the mobile ad newlinehoc network to provide Quality of Service. newlineIn this research work, an algorithm called Self Learning Ant colony newlineMultipath Routing (SLAMR) is proposed for improving node lifetime and newlineQuality of Service in the ad hoc network. Self learning is a vital part of an newlinealgorithm used to replace manual thresholds. Manual thresholds affect the newlineapplication performance and Quality of Service in an ad hoc network. newline