Abstract :
In this talk, I´ll present our results obtained from analyzing users´ mobility trace data. Unlike earlier work, we profile the movement patterns of wireless users and predict their locations, and show that each user regularly visits a list of places called hubs (e.g., buildings) with some probability. We also show that over a period of time (e.g., a week), a user may repeatedly follow a mixture of mobility profiles with certain probabilities associated with each of the profiles. Our analysis of the mobility trace data not only validate the existence of the so-called sociological orbits in users´ movement pattern, but also demonstrate the advantages of exploiting them in performing hub-level location predictions. As one of the potential applications of the mobility profiling, I will present a novel architecture that utilizes integrated cellular and ad hoc relaying (iCAR) to provide file downloading services to vehicles among other services in a Cyber Transportation System (ITS). I will also describe our recent effort on human-factors aware design of CTS applications, protocols and tools.
