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      Improved Location Estimation in Wireless Sensor Networks Using a Vector-Based Swarm Optimized Connected Dominating Set

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          Abstract

          Location estimation in wireless sensor networks (WSNs) has received tremendous attention in recent times. Improved technology and efficient algorithms systematically empower WSNs with precise location identification. However, while algorithms are efficient in improving the location estimation error, the factor of the network lifetime has not been researched thoroughly. In addition, algorithms are not optimized in balancing the load among nodes, which reduces the overall network lifetime. In this paper, we have proposed an algorithm that balances the load of computation for location estimation among the anchor nodes. We have used vector-based swarm optimization on the connected dominating set (CDS), consisting of anchor nodes for that purpose. In this algorithm, major tasks are performed by the base station with a minimum number of messages exchanged by anchor nodes and unknown nodes. The simulation results showed that the proposed algorithm significantly improves the network lifetime and reduces the location estimation error. Furthermore, the proposed optimized CDS is capable of providing a global optimum solution with a minimum number of iterations.

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          Differential evolution algorithm with ensemble of parameters and mutation strategies

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                Author and article information

                Journal
                Sensors (Basel)
                Sensors (Basel)
                sensors
                Sensors (Basel, Switzerland)
                MDPI
                1424-8220
                17 January 2019
                January 2019
                : 19
                : 2
                : 376
                Affiliations
                [1 ]Department of Computer Science and Engineering, Lovely Professional University, Jalandhar-Delhi GT Road, Phagwara 144 441, India; rsahaaot@ 123456gmail.com
                [2 ]Department of Electronics and Electrical Engineering, Lovely Professional University, Jalandhar-Delhi GT Road, Phagwara 144 441, India; raimritunjay@ 123456gmail.com (M.K.R.); khalsa128@ 123456gmail.com (J.S.P.S.)
                [3 ]Division of Research and Development, Lovely Professional University, Jalandhar-Delhi GT Road, Phagwara 144 441, India; rthomas.eyyalil@ 123456gmail.com
                [4 ]Department of Convergence Security, Sungshin Women’s University, Seoul 02844, Korea; taihoonn@ 123456daum.net
                [5 ]Department of Computer Engineering, Chonnam National University, 50 Daehak-ro, Yeosu 59626, Jeollanam-do, Korea; limsejung@ 123456korea.ac.kr
                Author notes
                [* ]Correspondence: gulshan3971@ 123456gmail.com ; Tel.: +91-814-652-4362
                Author information
                https://orcid.org/0000-0003-0026-149X
                https://orcid.org/0000-0003-0117-8102
                https://orcid.org/0000-0003-3249-495X
                Article
                sensors-19-00376
                10.3390/s19020376
                6359153
                30658498
                5ed5787a-1fb9-4326-a729-e0fbc0f4682c
                © 2019 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 12 November 2018
                : 12 January 2019
                Categories
                Article

                Biomedical engineering
                localization,accuracy,load balance,swarm optimization,network lifetime
                Biomedical engineering
                localization, accuracy, load balance, swarm optimization, network lifetime

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