The unique characteristic of the underwater acoustic communication channel force development of new protocols for underwater acoustic sensor networks. Especially, the pretty slower propagation speed of acoustic signals in underwater should be taken into consideration. This paper constructs a link scheduling model on MAC layer for multi-hop underwater acoustic sensor networks. The proposed model employs correlation matrix to describe the conflicts relationship among links and uses propagation delay to generate conflict matrix for collision detection. In order to minimum the frame length, a power control strategy is introduced and aimed to reduce the effect of link interference. Then, a heuristic algorithm is presented to solve the conflict-free problem based on the model. Simulation results show that the link scheduling method and the power control strategy can effectively improve network performance with respect to throughput and end to end delay.
The packets carried along a pre-defined route in underwater sensor networks are very vulnerble. Node mobility or intermittent channel availability easily leads to unreachable routing. Opportunistic routing has been proven to be a promising paradigm to design routing protocols for underwater sensor networks. It takes advantage of the broadcast nature of the wireless medium to combat packet losses and selects potential paths on the fly. Finding an appropriate forwarding candidate set is a key issue in opportunistic routing. Many existing solutions ignore the impact of candidates location distribution on packet forwarding. In this paper, a path diversity improved candidate selection strategy is applied in opportunistic routing to improve packet forwarding efficiency. It not only maximizes the packet forwarding advancements but also takes the candidate’s location distribution into account. Based on this strategy, we propose two effective routing protocols: position improved candidates selection (PICS) and position random candidates selection (PRCS). PICS employs two-hop neighbor information to make routing decisions. PRCS only uses one-hop neighbor information. Simulation results show that both PICS and PRCS can significantly improve network performance when compared with the previous solutions, in terms of packet delivery ratio, average energy consumption and end-to-end delay.
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