Probabilistic Optimal Path Routing Strategy for Delay Tolerant Networks

Abstract

Recent times have observed a huge growth in terms of the usage of Delay Tolerant Networks (DTN) due to the diversified generation and sharing of contents. The traditional methods for content generation and sharing have come a long way in the last decade and the recent trends demonstrates higher magnitude of data generation with rich and memory heavy contents. Also, the recent trend demonstrates that the content creator’s expectation on geographically diversified channels to share contents from remote locations. This demands improvements of the traditional methods for DTN routings. A good number of parallel researches have demonstrated many novel routing strategies in the recent time. Nonetheless, these parallel research outcomes are bottlenecked by the foundational challenge of DT networks as the DTNs are fundamentally delay appreciating or approving strategies, thus allows higher memory capabilities in the local nodes. Nevertheless, looking at the recent demand of the research, this characteristics of DTN has to be converted to a benefit for building a higher performing routing strategy to reduce not only the delay, rather also improve the overall routing time, reduce energy and improve memory awareness during the routing process. Hence, this work proposes a novel algorithm for finding the optimal path using multiple characteristics with probabilistic theories to improve the routing experience on DTNs. The outcome of this research demonstrates nearly 35% reduction in the routing path, nearly 57% reduction in the energy consumption, close to 85% improvement of network sustainability and 1.5 times improvement on network performance compared with the parallel benchmarked research outcomes.