{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T03:31:51Z","timestamp":1760239911999,"version":"build-2065373602"},"reference-count":45,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2019,1,17]],"date-time":"2019-01-17T00:00:00Z","timestamp":1547683200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>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.<\/jats:p>","DOI":"10.3390\/s19020376","type":"journal-article","created":{"date-parts":[[2019,1,17]],"date-time":"2019-01-17T11:30:27Z","timestamp":1547724627000},"page":"376","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Improved Location Estimation in Wireless Sensor Networks Using a Vector-Based Swarm Optimized Connected Dominating Set"],"prefix":"10.3390","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0026-149X","authenticated-orcid":false,"given":"Gulshan","family":"Kumar","sequence":"first","affiliation":[{"name":"Department of Computer Science and Engineering, Lovely Professional University, Jalandhar-Delhi GT Road, Phagwara 144 441, India"}]},{"given":"Rahul","family":"Saha","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Lovely Professional University, Jalandhar-Delhi GT Road, Phagwara 144 441, India"}]},{"given":"Mritunjay Kumar","family":"Rai","sequence":"additional","affiliation":[{"name":"Department of Electronics and Electrical Engineering, Lovely Professional University, Jalandhar-Delhi GT Road, Phagwara 144 441, India"}]},{"given":"Reji","family":"Thomas","sequence":"additional","affiliation":[{"name":"Division of Research and Development, Lovely Professional University, Jalandhar-Delhi GT Road, Phagwara 144 441, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0117-8102","authenticated-orcid":false,"given":"Tai-Hoon","family":"Kim","sequence":"additional","affiliation":[{"name":"Department of Convergence Security, Sungshin Women\u2019s University, Seoul 02844, Korea"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3249-495X","authenticated-orcid":false,"given":"Se-Jung","family":"Lim","sequence":"additional","affiliation":[{"name":"Department of Computer Engineering, Chonnam National University, 50 Daehak-ro, Yeosu 59626, Jeollanam-do, Korea"}]},{"given":"Jai Sukh Paul","family":"Singh","sequence":"additional","affiliation":[{"name":"Department of Electronics and Electrical Engineering, Lovely Professional University, Jalandhar-Delhi GT Road, Phagwara 144 441, India"}]}],"member":"1968","published-online":{"date-parts":[[2019,1,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"599","DOI":"10.1007\/978-3-319-04960-1_52","article-title":"A Review on Localization in Wireless Sensor Networks","volume":"Volume 264","author":"Kuriakose","year":"2014","journal-title":"Advances in Signal Processing and Intelligent Recognition Systems"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Alrajeh, N.A., Bashir, M., and Shams, B. (2013). Localization techniques in wireless sensor networks. Int. J. Distrib. Sens. Netw.","DOI":"10.1155\/2013\/304628"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"He, J.S., Ji, S., Li, Y., and Pan, Y. (2013). Wireless Ad Hoc and Sensor Networks: Management, Performance, and Applications, CRC Press.","DOI":"10.1201\/b15325"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Asgarnezhad, R., and Torkestani, J.A. (2011, January 9\u201311). A survey on backbone formation algorithms for Wireless Sensor Networks: (A New Classification). Proceedings of the Australasian Telecommunication Networks and Applications Conference (ATNAC), Melbourne, Australia.","DOI":"10.1109\/ATNAC.2011.6096632"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"828","DOI":"10.1109\/COMST.2017.2650979","article-title":"A Survey of Network Lifetime Maximization Techniques in Wireless Sensor Networks","volume":"19","author":"Yetgin","year":"2017","journal-title":"IEEE Commun. Surv. Tutor."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"550","DOI":"10.1109\/COMST.2016.2610578","article-title":"A Survey of Multi-Objective Optimization in Wireless Sensor Networks: Metrics, Algorithms, and Open Problems","volume":"19","author":"Fei","year":"2017","journal-title":"IEEE Commun. Surv. Tutor."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.jnca.2017.01.001","article-title":"A survey on non-linear optimization problems in wireless sensor networks","volume":"82","year":"2017","journal-title":"J. Netw. Comput. Appl."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1016\/j.cie.2016.08.028","article-title":"A survey of optimization algorithms for wireless sensor network lifetime maximization","volume":"101","author":"Curry","year":"2016","journal-title":"Comput. Ind. Eng."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"2172","DOI":"10.1016\/j.adhoc.2013.04.009","article-title":"Load balancing techniques for lifetime maximizing in wireless sensor networks","volume":"11","author":"Kacimi","year":"2013","journal-title":"Ad Hoc Netw."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Lim, K.S., Buyamin, S., Ahmad, A., Shapiai, M.I., Naim, F., Mubin, M., and Kim, D.H. (2014). Improving vector evaluated particle swarm optimisation using multiple nondominated leaders. Sci. World J., 2014.","DOI":"10.1155\/2014\/364179"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"626","DOI":"10.1109\/LCOMM.2004.835319","article-title":"The Cramer-Rao bounds of hybrid TOA\/RSS and TDOA\/RSS location estimation schemes","volume":"8","author":"Catovic","year":"2004","journal-title":"IEEE Commun. Lett."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Tomic, S., Beko, M., Dinis, R., and Bernardo, L. (2018). On Target Localization Using Combined RSS and AoA Measurements. Sensors, 18.","DOI":"10.3390\/s18041266"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Panichcharoenrat, T., and Lee, W. (2014, January 30\u201331). Two hybrid RSS\/TOA localization techniques in cognitive radio system. Proceedings of the 6th International Conference on Knowledge and Smart Technology (KST), Chonburi, Thailand.","DOI":"10.1109\/KST.2014.6775388"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Tiwari, S., Wang, D., Fattouche, M., and Ghannouchi, F. (2012). A Hybrid RSS\/TOA Method for 3D Positioning in an Indoor Environment. ISRN Signal Process., 2012.","DOI":"10.5402\/2012\/503707"},{"key":"ref_15","unstructured":"Naseri, H., and Koivunen, V. (2017). A Bayesian algorithm for distributed network localization using distance and direction data. IEEE Trans. Wirel. Commun."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"2227","DOI":"10.1109\/TII.2017.2695583","article-title":"Bayesian Networks in Fault Diagnosis","volume":"13","author":"Cai","year":"2017","journal-title":"IEEE Trans. Ind. Inform."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Cai, B., Kong, X., Liu, Y., Lin, J., Yuan, X., Xu, H., and Ji, R. (2018). Application of Bayesian Networks in Reliability Evaluation. IEEE Trans. Ind. Inform.","DOI":"10.1109\/TII.2018.2858281"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"771","DOI":"10.1016\/j.protcy.2012.10.093","article-title":"Energy Efficient Load-Balanced Clustering Algorithm for Wireless Sensor Networks","volume":"6","author":"Kuila","year":"2012","journal-title":"Procedia Technol."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1498","DOI":"10.1109\/JSEN.2012.2227704","article-title":"Load-Balanced Clustering Algorithm with Distributed Self- Organization for Wireless Sensor Networks","volume":"13","author":"Liao","year":"2013","journal-title":"IEEE Sens. J."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1016\/j.tcs.2012.11.020","article-title":"Approximation algorithms for load-balanced virtual backbone construction in wireless sensor networks","volume":"507","author":"He","year":"2013","journal-title":"Theor. Comput. Sci."},{"key":"ref_21","first-page":"9","article-title":"A Genetic Algorithm Inspired Load Balancing Protocol for Congestion Control in Wireless Sensor Networks using Trust Based Routing Framework","volume":"5","author":"Raha","year":"2013","journal-title":"Int. J. Comput. Netw. Inf. Secur."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Singh, V.K., and Sharma, V. (2014). Elitist Genetic Algorithm Based Energy Balanced Routing Strategy to Prolong Lifetime of Wireless Sensor Networks. Chin. J. Eng., 2014.","DOI":"10.1155\/2014\/437625"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1007\/s11571-014-9324-y","article-title":"An improved localization algorithm based on genetic algorithm in wireless sensor networks","volume":"9","author":"Peng","year":"2015","journal-title":"Cogn. Neurodyn."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"182","DOI":"10.1016\/j.ifacol.2016.12.031","article-title":"Wireless Sensor Network Lifespan Optimization with Simple, Rotated, Order and Modified Partially Matched Crossover Genetic Algorithms","volume":"49","author":"Ahmed","year":"2016","journal-title":"IFAC-PapersOnLine"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"731894","DOI":"10.1155\/2015\/731894","article-title":"A hybrid algorithm of GA + simplex method in the WSN localization","volume":"11","author":"Wang","year":"2015","journal-title":"Int. J. Distrib. Sens. Netw."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1002\/ett.2797","article-title":"Constructing load-balanced virtual backbones in probabilistic wireless sensor networks via multi-objective genetic algorithm","volume":"26","author":"He","year":"2015","journal-title":"Trans. Emerg. Telecommun. Technol."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Wani, S.M., and Nalbalwar, S.L. (2016, January 3\u20135). Identification of Balanced Node for Data Aggregation in Wireless Sensor Network. Proceedings of the International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT), Chennai, India.","DOI":"10.1109\/ICEEOT.2016.7755113"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"604","DOI":"10.1016\/j.adhoc.2011.11.003","article-title":"LIS: Localization based on an intelligent distributed fuzzy system applied to a WSN","volume":"10","author":"Larios","year":"2012","journal-title":"Ad Hoc Netw."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1016\/j.eswa.2015.12.007","article-title":"Distributed efficient localization in swarm robotics using Min-Max and Particle Swarm Optimization","volume":"50","author":"Nedjah","year":"2016","journal-title":"Expert Syst. Appl."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"2169","DOI":"10.1016\/j.ijleo.2015.11.117","article-title":"A modified ant colony optimization algorithm (mACO) for energy efficient wireless sensor networks","volume":"127","author":"Sharma","year":"2016","journal-title":"Optik Int. J. Light Electron Opt."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1016\/j.jnca.2014.02.011","article-title":"In-cluster vector evaluated particle swarm optimization for distributed regression in WSNs","volume":"42","author":"Shakibian","year":"2014","journal-title":"J. Netw. Comput. Appl."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Zeng, T., Hua, Y., Zhao, X., and Liu, T. (2016, January 9\u201312). Research on Glowworm swarm optimization localization algorithm based on wireless sensor network. Proceedings of the IEEE International Frequency Control Symposium (IFCS), New Orleans, LA, USA.","DOI":"10.1109\/FCS.2016.7546730"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"72","DOI":"10.1016\/j.neucom.2013.01.032","article-title":"A dynamic neural network approach for solving nonlinear inequalities defined on a graph and its application to distributed, routing-free, range-free localization of WSNs","volume":"117","author":"Li","year":"2013","journal-title":"Neurocomputing"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1016\/j.engappai.2015.12.015","article-title":"A machine learning approach for user localization exploiting connectivity data","volume":"50","author":"Cottone","year":"2016","journal-title":"Eng. Appl. Artif. Intell."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Cespedes-mota, A., Castanfnon, G., Martinez-herrera, A.F., and Cardenas-barron, L.E. (2016). Optimization of the Distribution and Localization of Wireless Sensor Networks Based on Differential Evolution Approach. Math. Probl. Eng., 7918581.","DOI":"10.1155\/2016\/7918581"},{"key":"ref_36","unstructured":"(2018, October 01). Free Sace Mdel. Available online: https:\/\/www.isi.edu\/nsnam\/ns\/doc\/node217.html."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1016\/j.jnca.2016.11.013","article-title":"An energy efficient and optimized load balanced localization method using CDS with one-hop neighbourhood and genetic algorithm in WSNs","volume":"78","author":"Kumar","year":"2017","journal-title":"J. Netw. Comput. Appl."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"390","DOI":"10.1016\/j.asoc.2012.08.014","article-title":"A differential evolution algorithm with intersect mutation operator","volume":"13","author":"Zhou","year":"2013","journal-title":"Appl. Soft Comput. J."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"600","DOI":"10.1016\/j.asoc.2012.08.035","article-title":"Adaptive directed mutation for real-coded genetic algorithms","volume":"13","author":"Tang","year":"2013","journal-title":"Appl. Soft Comput. J."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"5129","DOI":"10.1016\/j.asoc.2011.05.046","article-title":"Particle swarm algorithm with hybrid mutation strategy","volume":"11","author":"Gao","year":"2011","journal-title":"Appl. Soft Comput. J."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Haupt, R.L., and Haupt, S.E. (2004). Practical Genetic Algorithms, John Wiley & Sons, Inc.. [2nd ed.].","DOI":"10.1002\/0471671746"},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Price, K.V. (2013). Differential Evolution. Intell. Syst. Ref. Libr.","DOI":"10.1007\/978-3-642-30504-7_8"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"3021","DOI":"10.1016\/j.asoc.2010.12.001","article-title":"A modified Artificial Bee Colony (ABC) algorithm for constrained optimization problems","volume":"11","author":"Karaboga","year":"2011","journal-title":"Appl. Soft Comput. J."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"1679","DOI":"10.1016\/j.asoc.2010.04.024","article-title":"Differential evolution algorithm with ensemble of parameters and mutation strategies","volume":"11","author":"Mallipeddi","year":"2011","journal-title":"Appl. Soft Comput. J."},{"key":"ref_45","unstructured":"Madsen, K., Nielsen, H.B., and Tingleff, O. (2004). Methods For Non-Linear Least Squares Problems, Informatics and Mathematical Modelling Technical University of Denmark."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/2\/376\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T12:26:54Z","timestamp":1760185614000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/2\/376"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,1,17]]},"references-count":45,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2019,1]]}},"alternative-id":["s19020376"],"URL":"https:\/\/doi.org\/10.3390\/s19020376","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2019,1,17]]}}}