A Hybrid Range-free Algorithm Using Dynamic Communication Range for Wireless Sensor Networks

Han, Fang; Mohamed, Izzeldin Ibrahim; Liu, Xinni; Ghazali, Kamarul Hawari; Wang, Hao

doi:10.3991/ijoe.v16i08.14379

Cited by 3 publications

(2 citation statements)

References 14 publications

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“…Studied in [41][42][43] have indicated that the localization error is quite large even the three points are not strictly collinear. So, the condition of collinearity is express in Equation (27).…”

Section: Weighted Least Square Methodsmentioning

confidence: 99%

Optimized Range-Free Localization Scheme Using Autonomous Groups Particles Swarm Optimization for Anisotropic Wireless Sensor Networks

et al. 2023

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Location information is a required concern in localization-based service application in the field of wireless sensor networks (WSNs). Distance Vector-Hop (DV-Hop) algorithm as the most typical rangefree localization scheme is much fitter for large-scaled WSNs. Its localization performance is good in even distributed networks. However, it demonstrated extremely poor accuracy under anisotropic networks. It is an urgent problem that need to be addressed. Accordingly, an optimized DV-Hop localization algorithm is put forward in this study with considering several anisotropic factors. Accumulated hop size error and collinearity are two main reason that led to low accuracy and poor stability. Hence, hop size error of anchors is reduced by introducing distance gap based on anchors. Besides, weighted least square method is adopted to replace the least square method to against anisotropic factors caused by irregular radio patterns. Moreover, an Autonomous Groups Particles Swarm Optimization (AGPSO) is employed to further optimize the obtained coordinate in the first round. It developed a novel method to determine localization coverage. The localization coverage is also added to be one evaluation metric in our study, which makes up for the lack of this evaluation indicator in most of the studies. Simulation results display good localization accuracy and strong stability under anisotropic networks. In addition, it also concluded that metaheuristic optimization algorithm and weighted least square method are more suitable to conquer anisotropic factor. It briefly points out a new direction for the future research work in the localization area under anisotropic networks.

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Section: Weighted Least Square Methodsmentioning

confidence: 99%

Optimized Range-Free Localization Scheme Using Autonomous Groups Particles Swarm Optimization for Anisotropic Wireless Sensor Networks

et al. 2023

Self Cite

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“…Based on the literature, these proposed technologies improve the network life system but it takes more time as compared to other techniques [16]. Energy consumption is one of the main challenges in WSN technology.…”

Section: Related Workmentioning

confidence: 99%

Energy Efficient Strategy for WSN Technology Using Modified HGAF Technique

Aznaoui

Raghay²,

Ullah

et al. 2021

Int. J. Onl. Eng.

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<p class="0affiliation">Due to the rapid growth in technologies has led to the development of sensor nodes. As we know that wireless sensor network is collection of small and large number of sensor node. These sensor nodes are used for different domain like environmental research, health care, monitor, military, and record the physical activity. These nodes communicate with each other and forward the message to base station. For communication of these node different algorithms used Geographical adaptive fidelity (GAF) is one of them. Dropping energy utilization in wireless sensor network directly affects the network lifetime. HGAF is one of the important multiple location based on routing system algorithm. The main function of HGAF technique is to turn-off the unnecessary nodes in the network without interrupting the other connected node. In this paper we proposed a technique known as modified HGAF and it design as a power saving method. In the proposed technique the size of cell structure in grid changed and communication method improve due to those changes. Based on the result the proposed technique increase 25% in dead node ratio and also increase the network.</p>

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Effect of fitness function on localization performance in range-free localization algorithm

Han

Mohamed

Ghazali

et al. 2023

Multimed Tools Appl

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A Hybrid Range-free Algorithm Using Dynamic Communication Range for Wireless Sensor Networks

Cited by 3 publications

References 14 publications

Optimized Range-Free Localization Scheme Using Autonomous Groups Particles Swarm Optimization for Anisotropic Wireless Sensor Networks

Optimized Range-Free Localization Scheme Using Autonomous Groups Particles Swarm Optimization for Anisotropic Wireless Sensor Networks

Energy Efficient Strategy for WSN Technology Using Modified HGAF Technique

Effect of fitness function on localization performance in range-free localization algorithm

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