{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T23:28:08Z","timestamp":1784158088680,"version":"3.55.0"},"reference-count":28,"publisher":"Engineering and Technology Publishing","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["jcm"],"published-print":{"date-parts":[[2021]]},"abstract":"<jats:p>Localization is one of the important matters for Wireless Sensor Networks (WSN) because various applications are depending on exact sensor nodes position. The problem in localization is the gained low accuracy in estimation process. Thus, this research is intended to increase the accuracy by overcome the problem in the Global best Local Neighborhood Particle Swarm Optimization (GbLN-PSO) to gain high accuracy. To compass this problem, an Improved Global best Local Neighborhood Particle Swarm Optimization (IGbLN-PSO) algorithm has been proposed. In IGbLN-PSO algorithm, there are consists of two phases: Exploration phase and Exploitation phase. The neighbor particles population that scattered around the main particles, help in the searching process to estimate the node location more accurately and gained lesser computational time. Simulation results demonstrated that the proposed algorithm have competence result compared to PSO, GbLN-PSO and TLBO algorithms in terms of localization accuracy at 0.02%, 0.01% and 59.16%. Computational time result shows the proposed algorithm less computational time at 80.07%, 17.73% and 0.3% compared others.<\/jats:p>","DOI":"10.12720\/jcm.16.6.242-249","type":"journal-article","created":{"date-parts":[[2021,5,25]],"date-time":"2021-05-25T06:41:01Z","timestamp":1621924861000},"page":"242-249","source":"Crossref","is-referenced-by-count":15,"title":["Improved GbLN-PSO Algorithm for Indoor Localization in Wireless Sensor Network"],"prefix":"10.12720","author":[{"name":"Soft Computing and Intelligent System Research Group Faculty of Computing, Universiti Malaysia Pahang, Pekan 26600, Malaysia","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"M.Shahkhir","family":"Mozamir","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rohani Binti Abu","family":"Bakar","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wan Isni Soffiah Wan","family":"Din","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zalili Binti","family":"Musa","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"4977","published-online":{"date-parts":[[2021]]},"reference":[{"key":"ref0","doi-asserted-by":"publisher","unstructured":"[1] R. Vallikannu, A. George, and S. K. Srivatsa, \"Autonomous localization based energy saving mechanism in indoor MANETs using ACO,\" J. Discret. Algorithms, vol. 33, pp. 19-30, 2015.","DOI":"10.1016\/j.jda.2014.11.001"},{"key":"ref1","doi-asserted-by":"publisher","unstructured":"[2] J. H. Huh and K. Seo, \"An indoor location-based control system using bluetooth beacons for IoT systems,\" Sensors (Switzerland), vol. 17, no. 12, 2017.","DOI":"10.3390\/s17122917"},{"key":"ref2","doi-asserted-by":"publisher","unstructured":"[3] M. S. Mozamir, R. B. A. Bakar, and W. I. S. W. Din, \"Indoor localization estimation techniques in wireless sensor network: A review,\" in Proc. IEEE Int. Conf. Autom. Control Intell. Syst. I2CACIS 2018, 2019, pp. 148-154.","DOI":"10.1109\/I2CACIS.2018.8603685"},{"key":"ref3","unstructured":"[4] P. Z. Sotenga, K. Djouani, A. M. Kurien, and M. Mwila, \"Implementation of an indoor localisation algorithm for Internet of Things,\" Futur. Gener. Comput. Syst., 2018."},{"key":"ref4","unstructured":"[5] I. F. M. Zain and S. Y. Shin, \"Distributed localization for wireless sensor networks using binary particle swarm optimization (BPSO),\" in Proc. IEEE Veh. Technol. Conf., vol. 2015-Janua, no. 1, pp. 1-5, 2014."},{"key":"ref5","doi-asserted-by":"publisher","unstructured":"[6] X. Fang, Z. Jiang, L. Nan, and L. Chen, \"Noise-aware localization algorithms for wireless sensor networks based on multidimensional scaling and adaptive Kalman filtering,\" Comput. Commun., vol. 101, pp. 57-68, 2017.","DOI":"10.1016\/j.comcom.2016.10.011"},{"key":"ref6","doi-asserted-by":"publisher","unstructured":"[7] D. I. Vilaseca and J. I. Giribet, \"Indoor navigation using WiFi signals,\" in Proc. 4th Argentine Symposium and Conference on Embedded Systems, SASE\/CASE 2013, 2013, pp. 38-43.","DOI":"10.1109\/SASE-CASE.2013.6636772"},{"key":"ref7","doi-asserted-by":"publisher","unstructured":"[8] C. D and T. Jayabarathi, \"Wireless sensor networks node localization-a performance comparison of shuffled frog leaping and firefly algorithm in LabVIEW,\" Telkomnika Indones. J. Electr. Eng., vol. 14, no. 3, pp. 516-524, 2015.","DOI":"10.11591\/telkomnika.v14i3.7861"},{"key":"ref8","unstructured":"[9] O. Oguejiofor, A. Aniedu, H. Ejiofor, and A. Okolibe, \"Trilateration based localization algorithm for wireless sensor network,\" Int. J. Sci. Mod. Eng, no. 10, pp. 21-27, 2013."},{"key":"ref9","doi-asserted-by":"publisher","unstructured":"[10] G. Oliva, S. Panzieri, F. Pascucci, and R. Setola, \"Sensor networks localization: Extending trilateration via shadow edges,\" IEEE Trans. Automat. Contr., vol. 60, no. 10, pp. 2752-2755, 2015.","DOI":"10.1109\/TAC.2015.2404253"},{"key":"ref10","doi-asserted-by":"publisher","unstructured":"[11] J. Xu, J. He, Y. Zhang, F. Xu, and F. Cai, \"A distance-based maximum likelihood estimation method for sensor localization in wireless sensor networks,\" Int. J. Distrib. Sens. Networks, vol. 2016, pp. 1884-1888, 2016.","DOI":"10.2991\/icmmct-16.2016.375"},{"key":"ref11","doi-asserted-by":"publisher","unstructured":"[12] R. Misra, S. Shukla, and V. Chandel, \"Lightweight localization using trilateration for sensor networks,\" Int. J. Wirel. Inf. Networks, vol. 21, no. 2, pp. 89-100, 2014.","DOI":"10.1007\/s10776-014-0239-7"},{"key":"ref12","doi-asserted-by":"publisher","unstructured":"[13] H. H. Kenchannavar and S. Beedakar, \"Optimization techniques to improve lifetime of wireless sensor networks,\" pp. 446-450, 2015.","DOI":"10.1109\/ICESA.2015.7503389"},{"key":"ref13","doi-asserted-by":"publisher","unstructured":"[14] M. P. Wachowiak, M. C. Timson, and D. J. Duval, \"Adaptive particle swarm optimization with heterogeneous multicore parallelism and GPU acceleration,\" IEEE Trans. Parallel Distrib. Syst., vol. 28, no. 10, pp. 2784-2793, 2017.","DOI":"10.1109\/TPDS.2017.2687461"},{"key":"ref14","doi-asserted-by":"publisher","unstructured":"[15] R. Janapati, C. Balaswamy, and K. Soundararajan, \"Localization of cooperative WSN using distributed PSO with optimum references,\" Int. J. Electr. Comput. Eng., vol. 6, no. 6, pp. 3094-3102, 2016.","DOI":"10.11591\/ijece.v6i6.11427"},{"key":"ref15","doi-asserted-by":"publisher","unstructured":"[16] C. S. Shieh, V. O. Sai, Y. C. Lin, T. F. Lee, T. T. Nguyen, and Q. D. Le, \"Improved node localization for WSN using heuristic optimization approaches,\" in Proc. Int. Conf. Netw. Netw. Appl. NaNA 2016, no. 4, pp. 95-98, 2016.","DOI":"10.1109\/NaNA.2016.58"},{"key":"ref16","doi-asserted-by":"publisher","unstructured":"[17] C. Elkin, R. Kumarasiri, D. B. Rawat, and V. Devabhaktuni, \"Localization in wireless sensor networks: A dempster-shafer evidence theoretical approach,\" Ad Hoc Networks, vol. 54, pp. 30-41, 2017.","DOI":"10.1016\/j.adhoc.2016.09.020"},{"key":"ref17","doi-asserted-by":"publisher","unstructured":"[18] B. R. Stojkoska and V. Kirandziska, \"Improved MDS-based algorithm for nodes localization in wireless sensor networks,\" IEEE EuroCon 2013, pp. 608-613, 2013.","DOI":"10.1109\/EUROCON.2013.6625044"},{"key":"ref18","unstructured":"[19] Y. Zhang, H. Hu, W. Fu, and H. Jiang, \"Particle swarm optimization - based minimum residual algorithm for mobile robot localization in indoor environment,\" no. 3, pp. 1-9, 2017."},{"key":"ref19","doi-asserted-by":"publisher","unstructured":"[20] Z. Musa, M. Z. Salleh, R. A. Bakar, and J. Watada, \"GbLN-PSO and model-based particle filter approach for tracking human movements in large view cases,\" IEEE Trans. Circuits Syst. Video Technol., vol. 26, no. 8, pp. 1433-1446, 2016.","DOI":"10.1109\/TCSVT.2015.2433172"},{"key":"ref20","doi-asserted-by":"publisher","unstructured":"[21] M. S. Mozamir, R. Binti, A. Bakar, W. Isni, S. Wan, and Z. Musa, \"GbLN-PSO algorithm for indoor localization in wireless sensor network GbLN-PSO algorithm for indoor localization in wireless sensor network,\" 2020.","DOI":"10.12720\/jcm.16.6.242-249"},{"key":"ref21","unstructured":"[22] A. M. Zambrano-bigiarini and M. M. Zambrano-bigiarini, Package 'hydroPSO', 2018."},{"key":"ref22","doi-asserted-by":"publisher","unstructured":"[23] Z. Musa, M. H. B. M. Hassin, N. I. H. Fauzi, R. A. Bakar, and J. Watada, \"A new approach of optimal search solution in particle swarm optimization algorithm for object detection method,\" Adv. Sci. Lett., 2018.","DOI":"10.1166\/asl.2018.12999"},{"key":"ref23","doi-asserted-by":"publisher","unstructured":"[24] S. P. Singh and S. C. Sharma, \"A PSO based improved localization algorithm for wireless sensor network,\" Wirel. Pers. Commun., vol. 98, no. 1, pp. 487-503, 2018.","DOI":"10.1007\/s11277-017-4880-1"},{"key":"ref24","doi-asserted-by":"publisher","unstructured":"[25] V. Kaundal, P. Sharma, and M. Prateek, \"Wireless sensor node localization based on LNSM and hybrid TLBO-unilateral technique for outdoor location,\" Int. J. Electron. Telecommun., vol. 63, no. 4, pp. 389-397, 2017.","DOI":"10.1515\/eletel-2017-0054"},{"key":"ref25","doi-asserted-by":"publisher","unstructured":"[26] G. Sharma and A. Kumar, \"Improved DV-Hop localization algorithm using teaching learning based optimization for wireless sensor networks,\" Telecommun. Syst., vol. 67, no. 2, pp. 163-178, 2018.","DOI":"10.1007\/s11235-017-0328-x"},{"key":"ref26","unstructured":"[27] I. Strumberger, M. Beko, M. Tuba, and M. Minovic, Technological Innovation for Resilient Systems, vol. 521. Springer International Publishing, 2018."},{"key":"ref27","doi-asserted-by":"publisher","unstructured":"[28] I. Strumberger, M. Minovic, M. Tuba, and N. Bacanin, \"Performance of elephant herding optimization and tree growth algorithm adapted for node localization in wireless sensor networks,\" Sensors (Switzerland), vol. 19, no. 11, pp. 1-30, 2019.","DOI":"10.3390\/s19112515"}],"container-title":["Journal of Communications"],"original-title":[],"link":[{"URL":"http:\/\/www.jocm.us\/uploadfile\/2021\/0525\/20210525015209231.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,11,25]],"date-time":"2021-11-25T06:09:34Z","timestamp":1637820574000},"score":1,"resource":{"primary":{"URL":"http:\/\/www.jocm.us\/show-256-1663-1.html"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"references-count":28,"URL":"https:\/\/doi.org\/10.12720\/jcm.16.6.242-249","relation":{},"ISSN":["2374-4367"],"issn-type":[{"value":"2374-4367","type":"print"}],"subject":[],"published":{"date-parts":[[2021]]}}}