PSO based Amorphous algorithm to reduce localization error in Wireless Sensor Network

IF 3 3区 计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS
Pujasuman Tripathy, P.M. Khilar
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引用次数: 0

Abstract

In recent years, localizing or identifying the position of unknown sensor nodes has become an essential problem in Wireless Sensor Networks (WSN). The improvement in localization accuracy leads to obtaining the exact location of the dumb node. Among all localization algorithms, Amorphous localization is highly suggested for usage in many application domains due to its simplicity, viability, low cost, and zero additional hardware requirements. Position estimation of the dumb node in the Amorphous algorithm considers three different practical scenarios, such as the position of dumb nodes falling within the range of anchor nodes, the position of the dumb node being in the opposite direction of the anchor node, and the position of the dumb node not within the range of anchor node. However, the localization error generated by the Amorphous algorithm is high. To address the limitations of Amorphous algorithm we have proposed a PSO based Amorphous algorithm. The proposed work reduces the average hop size of anchor nodes and reduces the localization error. The simulation results demonstrate that, in comparison to other existing Amorphous algorithms, the proposed PSO based Amorphous localization algorithm produced a superior performance in terms of MAE, MSE and RMSE.

基于 PSO 的 Amourphous 算法减少无线传感器网络中的定位误差
近年来,定位或识别未知传感器节点的位置已成为无线传感器网络(WSN)中的一个重要问题。提高定位精度可以获得哑节点的准确位置。在所有定位算法中,非晶态定位因其简单、可行、低成本和零额外硬件要求而被广泛应用于许多应用领域。非定态算法中的哑节点位置估计考虑了三种不同的实际情况,例如哑节点的位置位于锚节点的范围内、哑节点的位置位于锚节点的反方向以及哑节点的位置不在锚节点的范围内。然而,Amorphous 算法产生的定位误差很大。针对 Amorphous 算法的局限性,我们提出了一种基于 PSO 的 Amorphous 算法。该算法减少了锚节点的平均跳数,降低了定位误差。仿真结果表明,与其他现有的 Amorphous 算法相比,所提出的基于 PSO 的 Amorphous 定位算法在 MAE、MSE 和 RMSE 方面性能更优。
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来源期刊
Pervasive and Mobile Computing
Pervasive and Mobile Computing COMPUTER SCIENCE, INFORMATION SYSTEMS-TELECOMMUNICATIONS
CiteScore
7.70
自引率
2.30%
发文量
80
审稿时长
68 days
期刊介绍: As envisioned by Mark Weiser as early as 1991, pervasive computing systems and services have truly become integral parts of our daily lives. Tremendous developments in a multitude of technologies ranging from personalized and embedded smart devices (e.g., smartphones, sensors, wearables, IoTs, etc.) to ubiquitous connectivity, via a variety of wireless mobile communications and cognitive networking infrastructures, to advanced computing techniques (including edge, fog and cloud) and user-friendly middleware services and platforms have significantly contributed to the unprecedented advances in pervasive and mobile computing. Cutting-edge applications and paradigms have evolved, such as cyber-physical systems and smart environments (e.g., smart city, smart energy, smart transportation, smart healthcare, etc.) that also involve human in the loop through social interactions and participatory and/or mobile crowd sensing, for example. The goal of pervasive computing systems is to improve human experience and quality of life, without explicit awareness of the underlying communications and computing technologies. The Pervasive and Mobile Computing Journal (PMC) is a high-impact, peer-reviewed technical journal that publishes high-quality scientific articles spanning theory and practice, and covering all aspects of pervasive and mobile computing and systems.
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