Indexed on: 27 Aug '15Published on: 27 Aug '15Published in: Personal and Ubiquitous Computing
Mobile opportunistic networks can realize self-organizing communications for complicated and dynamic scenarios, which makes them expected to support various applications. In this paper, we investigate how far the data can reach within time t (i.e., the dissemination distance), which reveals the tempo-spatial data dissemination properties of mobile opportunistic networks. Our investigations adopt the Brownian motion model and the Lévy mobility to characterize the movement patterns of nodes in the network. We select the Brownian motion model because it can be viewed as a limiting case of the random walk mobility model and the Markovian mobility model, and thus, our analytical results can be easily extended to these mobility models; We select the Lévy mobility since the movements of nodes are usually driven by human beings carrying the devices, and the Lévy mobility can closely mimic the walks of human beings, which makes our analysis more practical. In detail, we obtain the bounds of the distribution of the dissemination distance for the one-copy case and the multiple-copy case when nodes move with the Brownian motion and the Lévy mobility, respectively, which provide the potential of mobile opportunistic networks to support the services that may involve time and location sensitive data dissemination.