Optimizing Node Localization in Wireless Sensor Networks Based on Received Signal Strength Indicator
In order to improve the precision of inside localization and optimize the allocation of node resources in wireless sensor networks (WSNs), an equal-arc trilateral localization algorithm based on received signal strength indicator (RSSI) is proposed from the perspective of increasing measurement prec...
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Veröffentlicht in: | IEEE access 2019, Vol.7, p.73880-73889 |
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description | In order to improve the precision of inside localization and optimize the allocation of node resources in wireless sensor networks (WSNs), an equal-arc trilateral localization algorithm based on received signal strength indicator (RSSI) is proposed from the perspective of increasing measurement precision and bettering beacon nodes layout. The algorithm adopts Kalman filter to filter the data collected from the best communication range, thus the disturbance problem of RSSI value can be tackled easily. By analyzing the changeable relationship between the communication distance and the RSSI, an optimal communication distance can be identified to satisfy the application requirements. In this paper, an equal-arc triangular beacon node layout model is established to ensure that the motion tracks of unknown nodes are always situated within an optimal communication distance to improve the measurement precision. The experimental results show that the proposed work increases the average location accuracy of the equal-arc triangulation layout model by 81%, 54%, and 48%, respectively, compared with the traditional square beacon model, the traditional equilateral triangle beacon model, and the improved equilateral triangle beacon model. In comparison with the traditional triangular layout, the equal-arc layout area coverage is increased by 23%. |
doi_str_mv | 10.1109/ACCESS.2019.2920279 |
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The algorithm adopts Kalman filter to filter the data collected from the best communication range, thus the disturbance problem of RSSI value can be tackled easily. By analyzing the changeable relationship between the communication distance and the RSSI, an optimal communication distance can be identified to satisfy the application requirements. In this paper, an equal-arc triangular beacon node layout model is established to ensure that the motion tracks of unknown nodes are always situated within an optimal communication distance to improve the measurement precision. The experimental results show that the proposed work increases the average location accuracy of the equal-arc triangulation layout model by 81%, 54%, and 48%, respectively, compared with the traditional square beacon model, the traditional equilateral triangle beacon model, and the improved equilateral triangle beacon model. In comparison with the traditional triangular layout, the equal-arc layout area coverage is increased by 23%.</description><identifier>ISSN: 2169-3536</identifier><identifier>EISSN: 2169-3536</identifier><identifier>DOI: 10.1109/ACCESS.2019.2920279</identifier><identifier>CODEN: IAECCG</identifier><language>eng</language><publisher>Piscataway: IEEE</publisher><subject>Algorithms ; Communication ; equal-arc triangular ; Kalman filtering ; Kalman filters ; Layout ; Layouts ; Localization ; Mathematical model ; Model accuracy ; Nodes ; Optimization ; particle swarm algorithm ; Particle swarm optimization ; Received signal strength indicator ; RSSI ; Signal strength ; Triangles ; Triangulation ; Wireless communication ; Wireless networks ; Wireless sensor networks ; Zigbee</subject><ispartof>IEEE access, 2019, Vol.7, p.73880-73889</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2019</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c408t-411d4d7cf7efc0586258911b2419c31fb98e25b91174cb5a35ee147333a3d1b43</citedby><cites>FETCH-LOGICAL-c408t-411d4d7cf7efc0586258911b2419c31fb98e25b91174cb5a35ee147333a3d1b43</cites><orcidid>0000-0001-9474-6214</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/8727428$$EHTML$$P50$$Gieee$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,864,2100,4022,27632,27922,27923,27924,54932</link.rule.ids></links><search><creatorcontrib>Wang, Wei</creatorcontrib><creatorcontrib>Liu, Xuming</creatorcontrib><creatorcontrib>Li, Maozhen</creatorcontrib><creatorcontrib>Wang, Zhaoba</creatorcontrib><creatorcontrib>Wang, Cunhua</creatorcontrib><title>Optimizing Node Localization in Wireless Sensor Networks Based on Received Signal Strength Indicator</title><title>IEEE access</title><addtitle>Access</addtitle><description>In order to improve the precision of inside localization and optimize the allocation of node resources in wireless sensor networks (WSNs), an equal-arc trilateral localization algorithm based on received signal strength indicator (RSSI) is proposed from the perspective of increasing measurement precision and bettering beacon nodes layout. The algorithm adopts Kalman filter to filter the data collected from the best communication range, thus the disturbance problem of RSSI value can be tackled easily. By analyzing the changeable relationship between the communication distance and the RSSI, an optimal communication distance can be identified to satisfy the application requirements. In this paper, an equal-arc triangular beacon node layout model is established to ensure that the motion tracks of unknown nodes are always situated within an optimal communication distance to improve the measurement precision. The experimental results show that the proposed work increases the average location accuracy of the equal-arc triangulation layout model by 81%, 54%, and 48%, respectively, compared with the traditional square beacon model, the traditional equilateral triangle beacon model, and the improved equilateral triangle beacon model. In comparison with the traditional triangular layout, the equal-arc layout area coverage is increased by 23%.</description><subject>Algorithms</subject><subject>Communication</subject><subject>equal-arc triangular</subject><subject>Kalman filtering</subject><subject>Kalman filters</subject><subject>Layout</subject><subject>Layouts</subject><subject>Localization</subject><subject>Mathematical model</subject><subject>Model accuracy</subject><subject>Nodes</subject><subject>Optimization</subject><subject>particle swarm algorithm</subject><subject>Particle swarm optimization</subject><subject>Received signal strength indicator</subject><subject>RSSI</subject><subject>Signal strength</subject><subject>Triangles</subject><subject>Triangulation</subject><subject>Wireless communication</subject><subject>Wireless networks</subject><subject>Wireless sensor networks</subject><subject>Zigbee</subject><issn>2169-3536</issn><issn>2169-3536</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>ESBDL</sourceid><sourceid>RIE</sourceid><sourceid>DOA</sourceid><recordid>eNpNUV1LHDEUHUoFxfoLfAn0ebf53CSPdrF1YVFwFB9DPu5ssx0n2yS26K9v7Ij0vtzD4ZxzuZyuOyd4SQjWXy7W68u-X1JM9JJqiqnUH7oTSlZ6wQRbffwPH3dnpexxG9UoIU-6cHOo8TG-xGmHrlMAtE3ejvHF1pgmFCf0EDOMUArqYSopo2uof1L-WdBXWyCgJroFD_F3w33cTXZEfc0w7eoPtJlC9Lam_Kk7GuxY4Oxtn3b33y7v1leL7c33zfpiu_Acq7rghAQepB8kDB4LtaJCaUIc5UR7RganFVDhGiW5d8IyAUC4ZIxZFojj7LTbzLkh2b055Pho87NJNpp_RMo7Y3ONfgQjVlqKAHrwQXLgxGGFcXCDA-qUI6RlfZ6zDjn9eoJSzT495fZfMZQLIbQWDDcVm1U-p1IyDO9XCTav7Zi5HfPajnlrp7nOZ1cEgHeHklRyqthfofGLLg</recordid><startdate>2019</startdate><enddate>2019</enddate><creator>Wang, Wei</creator><creator>Liu, Xuming</creator><creator>Li, Maozhen</creator><creator>Wang, Zhaoba</creator><creator>Wang, Cunhua</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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The algorithm adopts Kalman filter to filter the data collected from the best communication range, thus the disturbance problem of RSSI value can be tackled easily. By analyzing the changeable relationship between the communication distance and the RSSI, an optimal communication distance can be identified to satisfy the application requirements. In this paper, an equal-arc triangular beacon node layout model is established to ensure that the motion tracks of unknown nodes are always situated within an optimal communication distance to improve the measurement precision. The experimental results show that the proposed work increases the average location accuracy of the equal-arc triangulation layout model by 81%, 54%, and 48%, respectively, compared with the traditional square beacon model, the traditional equilateral triangle beacon model, and the improved equilateral triangle beacon model. In comparison with the traditional triangular layout, the equal-arc layout area coverage is increased by 23%.</abstract><cop>Piscataway</cop><pub>IEEE</pub><doi>10.1109/ACCESS.2019.2920279</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0001-9474-6214</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Algorithms Communication equal-arc triangular Kalman filtering Kalman filters Layout Layouts Localization Mathematical model Model accuracy Nodes Optimization particle swarm algorithm Particle swarm optimization Received signal strength indicator RSSI Signal strength Triangles Triangulation Wireless communication Wireless networks Wireless sensor networks Zigbee |
title | Optimizing Node Localization in Wireless Sensor Networks Based on Received Signal Strength Indicator |
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