Personalized Prefetching for Manets

Mobile ad hoc networks (MANETs) are a very promising next generation networks. Prediction is an essential aspect in the deployment of MANETs. Current work mainly focuses on mobility prediction: prediction of spatio-temporal trajectories of nodes. Web page prefetching based on prediction of user´s behavior has been shown to decrease latency in wired networks-current models of prefetching focus on what to prefetch and not when. Since routing information changes with time in MANETs, the expected time of user´s access is also important. In this paper we integrate prefetching algorithms with mobility models and personalized to user browsing patterns. This not only reduces latency but also ensures just-in-time prefetching