With the rapid development of underwater acoustic modem technology, underwater acoustic sensor networks (UWASNs) have more applications in long-term monitoring of the deployment area. In the underwater environment, the sensors are costly with limited energy. And acoustic communication medium poses new challenges, including high path loss, low bandwidth, and high energy consumption. Therefore, designing transmission mechanism to decrease energy consumption and to optimize the lifetime of UWASN becomes a significant task. This paper proposes a balance transmission mechanism, and divides the data transmission process into two phases. In the routing set-up phase, an efficient routing algorithm based on the optimum transmission distance is present to optimize the energy consumption of the UWASN. And then, a data balance transmission algorithm is introduced in the stable data transmission phase. The algorithm determines one-hop or multihop data transmission of the node to underwater sink according to the current energy level of adjacent nodes. Furthermore, detailed theoretical analysis evaluates the optimum energy levels in the UWASNs with different scales. The simulation results prove the efficiency of the BTM.
Lifetime prolonging is one of the most significant issues in the research on underwater acoustic sensor networks (UASNs). Unbalanced energy consumption influences greatly the network lifetime. First this study discusses a probability-based energy balance (PEB) scheme. The sensor nodes report the data to the sink by single-hop direct transmission (DT) or by multi-hop transmission (MT) under the probabilities. A centralized probabilities finding algorithm (PFA) can find a set of transmission probabilities to better balance the energy consumption. Then, a suboptimal distance (SOD)-based data transmission scheme is proposed which is a distributed scheme and operates on each sensor node. It optimizes the slice width and selects the relays near the optimum transmission range. Simulations show that the two schemes can save more energy and prolong the network lifetime efficiently.
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