Fundamental Analysis on Data Dissemination in Mobile Opportunistic Networks With Lévy Mobility

Mobile opportunistic networks take advantage of contact opportunities due to the mobility of individual nodes for distributing data. Studying the inherent traits of data dissemination in mobile opportunistic networks can reveal their potential to support emerging applications, such as emergency services and mobile commerce. In this paper, we employ the Levy mobility model to characterize the movement pattern of nodes. Because the Levy mobility closely mimics human walking patterns, the analysis model that we adopt is realistic. Our analyses consider small- and large-scale perspectives. In the small-scale case, we investigate the distribution of the minimum time needed by the data to spread to a given region. In the large-scale case, we examine the probability bounds of the earliest time at which the data arrives in a region that is sufficiently far away. We also derive the rate at which such a probability tends to zero as the distance to the region increases to infinity. The results of extensive numerical simulations validate our analysis.