基于蚂蚁狮子优化算法的水声传感器网络能量感知节点部署

R. S. Kumar, G. Sivaradje
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引用次数: 0

摘要

水下无线传感器网络是随着无线传感器网络的普及而产生的。由于其广泛和即时的应用,它对研究产生了重大影响。然而,成功实现水下无线传感器网络存在许多挑战。水下传感器网络中最大的问题是传感器节点的能量消耗问题。本文采用蚁狮优化算法(Ant Lion optimization algorithm, ALOA)延长水下无线传感器网络的寿命,从内部子集群传感器节点收集信息,缩短中继节点的多跳传输距离。将海底网络区域建模为一组具有多个阶段的三维同心圆柱体。每个阶段也被分成许多块,每个块代表一个集群。所建议的算法以自下而上的垂直通信方式从海底到海面进行操作。由于对海底的强大水压造成的通信问题通过使用不同高度的水平来解决。仿真结果表明,该方法的吞吐量为297.99 kbps, PDR为46.34%,能耗为13%,丢包率为165.6 kbps。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Energy Aware Node deployment using Ant Lion optimization algorithm in underwater acoustic sensor Network
underwater wireless sensor networks were created as a result of the spread of wireless sensor networks. Because of its extensive and in-the-moment applications, it has had a significant impact on research. However, there are numerous challenges to successfully implementing underwater wireless sensor networks. The issue of energy depletion in sensor nodes is the biggest concern in the underwater sensor network. In this article, the Ant Lion optimization algorithm (ALOA) is employed to extend the lifespan of the underwater wireless sensor network, collect information from inner sub-cluster sensor nodes, and shorten the relay nodes’ multi-hop transmission distance. The undersea network area is modeled as a set of three-dimensional concentric cylinders with many stages. Each stage is also separated into a number of blocks, each of which represents a single cluster. The suggested algorithm operates in a bottom-up Vertical communication from the ocean floor to the surface. The communication problems caused by strong water pressure toward the sea floor are resolved by using many levels of differing heights. Simulations are run to demonstrate the effectiveness of the suggested approach, which performs better in terms of throughput of 297.99 kbps, PDR of 46.34%, energy usage of 13%, and packet loss of 165.6 kbps.
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