This paper describes a software-based tool that tracks mobile node roaming and infers the time-to-handover as well as the preferential handover target, based on behavior inference solely derived from regular usage data captured in visited wireless networks. The paper presents the tool architecture; computational background for mobility estimation; operational guidelines concerning how the tool is being used to track several aspects of roaming behavior in the context of wireless networks. Target selection accuracy is validated having as baseline traces obtained in realistic scenarios.
Mobile ad hoc networks (MANETs) are multihop networks that are capable of establishing communication in the absence of any pre-existing infrastructure. Due to frequent node mobility and unreliable wireless links, the network is characterized by unpredictable topological changes. For more robust and reliable communications, it is important that a mobile node anticipates address changes and predicts its future routes in the network. This Chapter describes prediction-based mobility management schemes for mobile ad hoc networks. We propose a Markov model-based mobility management scheme that provides an adaptive location prediction mechanism. We used simulation method to evaluate the prediction accuracy as well as the probability of making the correct predictions. The simulation results indicated that higher order Markov models have slightly greater prediction accuracy than lower order Markov models. However, the prediction accuracy decreases with increase in the probability of random movement both for network sizes and number of hops.