MFRD: A Novel Multi-Criteria Fusion Routing Decision Making Algorithm in Mobile Opportunistic Networks

Mobile opportunistic networks (MONs) have gained considerable attention in enabling impromptu communication due to the progress in communication technologies over the past decade. One of the main characteristics of MONs is their inconsistent connectivity and implicit end-to-end routing paths. This presents a challenge in making optimal routing decisions during message transmission, as we need to identify relay nodes that can reliably transport messages to their destinations quickly and cost-effectively. Here, we propose a novel multi-criteria fusion routing decision making algorithm (MFRD). Initially, we establish four metrics that measure the message transmission capability (MTC) of a node in terms of message throughput, message tolerance, geographic connectivity, and time connectivity. Next, we use the game theory mechanism to merge the DEMATEL subjective weights and the CRITIC objective weights of each metric, resulting in a more thorough integrated weight for them. Then, we integrate the benefits of two MCDM techniques, TOPSIS and GRA, to provide a new relative proximity measure for evaluating the MTC of alternative nodes. Finally, during message propagation, we select nodes with higher MTC as next-hop relays. The simulation results demonstrate that MFRD not only significantly improves the delivery rate and reduces the average latency, but it also shows excellent performance in network overhead and average hop count.