A novel segmented routing algorithm based on the markov decision process in mobile opportunistic networks

The purposes of research of routing algorithms in the mobile opportunistic networks are to improve the message delivery ratio, control overhead, and reduce the end-to-end delay. Now the performance of routing algorithms is very low because the opportunistic network structure is sparse and the network topology is variable. In this article, we use the Markov random process to propose a new segmented routing algorithm with a higher efficiency in opportunistic networks. In the stage of multicopy, we propose a forwarding strategy with the Markov decision process (MPD) to forward messages to multiple relay nodes quickly. In the stage of singe copy, we establish a precise delivery model to forward messages to the destination node with less relay nodes by combining the MPD with historical encountering information of nodes. The two-stage segmented routing algorithm not only balances the relationship between the delivery ratio and the network overhead, but also saves network resources. Compared with other routing algorithms, our proposed segmented routing algorithm is superior to the existing routing algorithms in the message delivery ratio, message delay, and network overhead. (c) 2018 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.