A Location Based Mobility Prediction Scheme for Post Disaster Communication Network using DTN

Selection of next hop forwarder plays a pivotal role in timely and accurate dissemination of post disaster situational data to a predetermined destination. Prior knowledge about the probability of future presence of a node near the destination eases this process significantly. In this paper, we propose a location based mobility prediction scheme that helps in selecting the appropriate forwarder by predicting the mobility pattern of nodes. Researchers, over a considerable period, have proposed the use of DTN in setting up a post disaster communication network. DTN specific user mobility involves both periodic and slightly chaotic patterns; chaotic behavior being attributed to the sudden causal events triggering instantaneous node mobility. In our approach, we approximate the periodicity of the DTN node mobility and use that knowledge to facilitate forwarding. Each mobile node in this approach is expected to periodically sample its own position in terms of time-location pair. This information is shared by other nodes upon contact. The sampled data, from other nodes, are extrapolated for future time instances to predict the possible locations of the mobile nodes for the next few points in time. So, the node having minimal distance around the vicinity of the destination, in some future time, qualify as the next forwarder. We compare the results, thus obtained, with real location of the nodes in future mentioned time instances and simulation results show that our scheme provides satisfactory results in predicting mobility of nodes to a great extent.