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提高无线传感器网络中的本地化效率和准确性。

Enhancing Localization Efficiency and Accuracy in Wireless Sensor Networks.

机构信息

Department of Computer Science & Information Technology, University of Malakand, Chakdara 18800, Pakistan.

Department of Software Engineering, University of Malakand, Chakdara 18800, Pakistan.

出版信息

Sensors (Basel). 2023 Mar 3;23(5):2796. doi: 10.3390/s23052796.

DOI:10.3390/s23052796
PMID:36904998
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10007187/
Abstract

Accuracy is the vital indicator in location estimation used in many scenarios, such as warehousing, tracking, monitoring, security surveillance, etc., in a wireless sensor network (WSN). The conventional range-free DV-Hop algorithm uses hop distance to estimate sensor node positions but has limitations in terms of accuracy. To address the issues of low accuracy and high energy consumption of DV-Hop-based localization in static WSNs, this paper proposes an enhanced DV-Hop algorithm for efficient and accurate localization with reduced energy consumption. The proposed method consists of three steps: first, the single-hop distance is corrected using the RSSI value for a specific radius; second, the average hop distance between unknown nodes and anchors is modified based on the difference between actual and estimated distances; and finally, the least-squares approach is used to estimate the location of each unknown node. The proposed algorithm, named Hop-correction and energy-efficient DV-Hop (HCEDV-Hop), is executed and evaluated in MATLAB to compare its performance with benchmark schemes. The results show that HCEDV-Hop improves localization accuracy by an average of 81.36%, 77.99%, 39.72%, and 9.96% compared to basic DV-Hop, WCL, improved DV-maxHop, and improved DV-Hop, respectively. In terms of message communication, the proposed algorithm reduces energy usage by 28% compared to DV-Hop and 17% compared to WCL.

摘要

在无线传感器网络(WSN)中,许多场景(如仓储、跟踪、监测、安全监控等)都需要使用定位精度作为关键指标。传统的无距离 DV-Hop 算法使用跳数来估计传感器节点的位置,但在精度方面存在局限性。为了解决基于 DV-Hop 的定位在静态 WSN 中精度低和能耗高的问题,本文提出了一种高效、准确、能耗低的增强型 DV-Hop 算法。该方法由三个步骤组成:首先,使用特定半径的 RSSI 值修正单跳距离;其次,根据实际和估计距离之间的差异,修改未知节点和锚节点之间的平均跳数;最后,使用最小二乘法估计每个未知节点的位置。该算法名为 Hop-correction 和 energy-efficient DV-Hop (HCEDV-Hop),在 MATLAB 中执行和评估,以比较其与基准方案的性能。结果表明,HCEDV-Hop 与基本 DV-Hop、WCL、改进的 DV-maxHop 和改进的 DV-Hop 相比,分别平均提高了 81.36%、77.99%、39.72%和 9.96%的定位精度。在消息通信方面,与 DV-Hop 相比,该算法减少了 28%的能耗,与 WCL 相比减少了 17%的能耗。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f263/10007187/e729aad9e73c/sensors-23-02796-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f263/10007187/d1e428728ad7/sensors-23-02796-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f263/10007187/1967134b70f8/sensors-23-02796-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f263/10007187/aba51754d40b/sensors-23-02796-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f263/10007187/13d15a16f2d8/sensors-23-02796-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f263/10007187/0e3e9f22f59d/sensors-23-02796-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f263/10007187/45c5269bc563/sensors-23-02796-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f263/10007187/86cd781e0904/sensors-23-02796-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f263/10007187/89289e4cb17b/sensors-23-02796-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f263/10007187/6c3fdcec8b5c/sensors-23-02796-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f263/10007187/fc5b19cf6a38/sensors-23-02796-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f263/10007187/e729aad9e73c/sensors-23-02796-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f263/10007187/d1e428728ad7/sensors-23-02796-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f263/10007187/c7d7c9ae3d02/sensors-23-02796-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f263/10007187/1967134b70f8/sensors-23-02796-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f263/10007187/aba51754d40b/sensors-23-02796-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f263/10007187/13d15a16f2d8/sensors-23-02796-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f263/10007187/0e3e9f22f59d/sensors-23-02796-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f263/10007187/45c5269bc563/sensors-23-02796-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f263/10007187/86cd781e0904/sensors-23-02796-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f263/10007187/89289e4cb17b/sensors-23-02796-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f263/10007187/6c3fdcec8b5c/sensors-23-02796-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f263/10007187/fc5b19cf6a38/sensors-23-02796-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f263/10007187/e729aad9e73c/sensors-23-02796-g012.jpg

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