Efficient Data Caching Based On Fuzzy Decision Routing In Vehicle Disruption Tolerant Networks

Abstract

Disruption tolerant networks (DTNs) are characterized by low node density, unpredictable node mobility, and lack of global network information. Most of current research efforts in DTNs focus on data forwarding, but only limited work have been done on providing efficient data access to vehicle users. The proposed Fuzzy Probabilistic Routing Protocol using History of Encounters and Transitivity (FPRoPHET) protocol uses an algorithm that attempts to exploit the non-randomness of real-world encounters by maintaining a set of probabilities for successful delivery to known destinations in the VDTN (delivery predictabilities) and replicating messages during opportunistic encounters only if the Mule that does not have the message appears to have a better chance of delivering it. Propose a novel approach to support fairness aware cooperative caching scheme in VSNs (Vehicle Social Networks). Through capturing close friend set of each node, we cache data prior at nodes which are overlapped by most nodes' close friend sets. Proposed system develop an optimization procedure to restrict the scope of caching nodes to satisfy the condition that there is at least one common node between caching node set and each node's close friend set. By this mean, we minimize the number of caching nodes while ensuring the fairness of each node at the same time. Extensive trace-driven simulations show that our approach significantly improves data access performance compared to existing schemes.