Recently, underwater acoustic sensor networks (UASNs) have been proposed to explore underwater environments for scientific, commercial, and military purposes. However, long propagation delays, high transmission losses, packet drops, and limited bandwidth in underwater propagation environments make realization of reliable and energy-efficient communication a challenging task for UASNs. To prolong the lifetime of battery-limited UASNs, two critical factors (i.e., packet size and transmission power) play vital roles. At one hand, larger packets are vulnerable to packet errors, while smaller packets are more resilient to such errors. In general, using smaller packets to avoid bit errors might be a good option. However, when small packets are used, more frames should be transmitted due to the packet fragmentation, and hence, network overhead and energy consumption increases. On the other hand, increasing transmission power reduces frame errors, but this would result in unnecessary energy consumption in the network. To this end, the packet size and transmission power should be jointly considered to improve the network lifetime. In this study, an optimization framework via an integer linear programming (ILP) has been proposed to maximize the network lifetime by joint optimization of the transmission power and packet size. In addition, a realistic link-layer energy consumption model is designed by employing the physical layer characteristics of UASNs. Extensive numerical analysis through the optimization model has been also performed to investigate the tradeoffs caused by the transmission power and packet size quantitatively.

中文翻译：

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水声传感器网络寿命最大化的数据包大小优化


最近，水声传感器网络（UASN）被提议用于探索水下环境，用于科学、商业和军事目的。然而，水下传播环境中的长传播延迟、高传输损耗、丢包和有限带宽使得实现可靠且节能的通信成为UASN的一项艰巨任务。为了延长电池受限的UASN的寿命，两个关键因素（即数据包大小和传输功率）发挥着至关重要的作用。一方面，较大的数据包容易受到数据包错误的影响，而较小的数据包对此类错误的恢复能力更强。一般来说，使用较小的数据包来避免误码可能是一个不错的选择。然而，当使用小数据包时，由于数据包碎片，需要传输更多的帧，因此网络开销和能量消耗增加。另一方面，增加传输功率可以减少帧错误，但这会导致网络中不必要的能量消耗。为此，应联合考虑数据包大小和传输功率，以提高网络寿命。在本研究中，提出了一种通过整数线性规划（ILP）的优化框架，通过传输功率和数据包大小的联合优化来最大化网络寿命。此外，利用UASN的物理层特性，设计了真实的链路层能耗模型。还通过优化模型进行了广泛的数值分析，以定量研究传输功率和数据包大小引起的权衡。