声学UWSNs的高效三次分层路径规划算法(EECPPA

A. Muhammad, Fan Wang, Zefeng Lv, Muhammad Asad, Samra Zafar, E. Munir, Xiaopeng Hu
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引用次数: 5

摘要

在本文中,我们将能效逻辑立方体分层路径规划算法(EECPPA)和多汇EECPPA (MSEECPPA)用于声学三维水下传感器网络(UWSNs)。EECPPA和MSEECPPA算法是完全分布式的,在逻辑划分的三维网络中执行时具有很高的采用率。所提出的模型在传感器位置变化时具有灵活性,并且具有在三维立方体uwsn中重新配置逻辑立方体大小的出色能力。这些多个逻辑多维数据集在选择多个组领导节点(称为簇头)中起着至关重要的作用。EECPPA和MSEECPPAA的迭代执行操作分为三个阶段,分别称为;NDP (Network Dimensional Phase)、NSP (Network settlement Phase)和NTP (Network Transmission Phase)。在第一阶段,构建多个立方体层,在第二阶段,在逻辑立方体边界的参考点附近选择领先节点,在NTP中,节点之间进行实际通信。MSEECPPA算法选择合适的中继节点称为多sink,利用多希望机制增加距离基站较远节点的生存期。大量的仿真实验提供了令人鼓舞的发现,所提出的模型在成功的数据包传递,更少的传播延迟和更好的网络生存时间方面优于DBR路由协议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Energy Efficient Cubical layered Path Planning Algorithm (EECPPA) for acoustic UWSNs
In this paper, we purpose Energy Efficient logical Cubical layered Path Planning Algorithm (EECPPA) and Multiple Sink EECPPA (MSEECPPA) for acoustic 3D Under Water Sensor Networks (UWSNs). EECPPA and MSEECPPA algorithms are completely distributed and highly adoptive in their execution in logical divided 3D networks into multiple cubes. Proposed models are flexible during location variations of sensors and have excellent ability to reconfigure the size of the logical cubes within 3D cubical UWSNs. These multiple logical cubes play vital role in selection of multiple group leading nodes, called Cluster Heads (CHs). The iterative executional operation of EECPPA and MSEECPPAA is divided into three phases called; Network Dimensional Phase (NDP), Network Settling Phase (NSP) and Network Transmission Phase (NTP). In first phase, multiple cubical layers are constructed, in second leading nodes are selected near the reference point of logical cube's boundaries and in NTP actual communications of the nodes take place. MSEECPPA algorithm selects the suitable relaying nodes called multiple sinks to utilize the multi-hoping mechanism to increase the lifetime of longer distance nodes from the Base Station (BS). Extensive simulation experiments provide the encouraging findings that proposed models outperform the DBR routing protocol in successful packet delivery, less propagational delay and better network lifetime.
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