p-A Multi-metric Decision Theory Based Adaptive Routing for Mobile Sparse Underwater Acoustic Sensor Network

Mobile and sparse underwater acoustic sensor networks (MS-UASNs) have attracted much attention due to their wide applications in various fields. However, void holes caused by the movement of nodes and the sparse deployment of networks, pose many challenges to design reliable routing protocol for MS-UASNs. Thereby, selecting the next-hop forwarder merely according to the state of current node may lead to the failure of forwarding in the local sparse region. To deal with the problem of void holes in sparse networks, in this paper we propose a Multi-metric decision theory based adaptive routing protocol (MDARP). The novelty of MDARP is that the selection of relay candidate nodes considers not only the depth of expected next hop, but also the continuable degree (CD) of all subsequent hops. By this method, the probability of encountering voids is reduced effectively. Meanwhile, the source node evaluates the quality of candidates by taking into account the CD, stable degree (SD) and energy cost (EC) based on Multi-metric decision theory (M2DT), and then the optimal next hop is determined. Subsequently, the source node enables to schedule the packets transmission toward the destination efficiently based on the quality of nodes. The simulation results represent that the MDARP protocol shows better performance in terms of packet delivery ratio, energy efficiency and end-to-end delay in MS-UASNs.