{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,7]],"date-time":"2026-05-07T14:40:13Z","timestamp":1778164813752,"version":"3.51.4"},"reference-count":53,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2023,7,24]],"date-time":"2023-07-24T00:00:00Z","timestamp":1690156800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"project SP2023\/074 Application of Machine and Process Control Advanced Methods"},{"name":"Ministry of Education, Youth, and Sports, Czech Republic"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The cluster technique involves the creation of clusters and the selection of a cluster head (CH), which connects sensor nodes, known as cluster members (CM), to the CH. The CH receives data from the CM and collects data from sensor nodes, removing unnecessary data to conserve energy. It compresses the data and transmits them to base stations through multi-hop to reduce network load. Since CMs only communicate with their CH and have a limited range, they avoid redundant information. However, the CH\u2019s routing, compression, and aggregation functions consume power quickly compared to other protocols, like TPGF, LQEAR, MPRM, and P-LQCLR. To address energy usage in wireless sensor networks (WSNs), heterogeneous high-power nodes (HPN) are used to balance energy consumption. CHs close to the base station require effective algorithms for improvement. The cluster-based glow-worm optimization technique utilizes random clustering, distributed cluster leader selection, and link-based routing. The cluster head routes data to the next group leader, balancing energy utilization in the WSN. This algorithm reduces energy consumption through multi-hop communication, cluster construction, and cluster head election. The glow-worm optimization technique allows for faster convergence and improved multi-parameter selection. By combining these methods, a new routing scheme is proposed to extend the network\u2019s lifetime and balance energy in various environments. However, the proposed model consumes more energy than TPGF, and other protocols for packets with 0 or 1 retransmission count in a 260-node network. This is mainly due to the short INFO packets during the neighbor discovery period and the increased hop count of the proposed derived pathways. Herein, simulations are conducted to evaluate the technique\u2019s throughput and energy efficiency.<\/jats:p>","DOI":"10.3390\/s23146639","type":"journal-article","created":{"date-parts":[[2023,7,25]],"date-time":"2023-07-25T01:32:10Z","timestamp":1690248730000},"page":"6639","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Contextual Cluster-Based Glow-Worm Swarm Optimization (GSO) Coupled Wireless Sensor Networks for Smart Cities"],"prefix":"10.3390","volume":"23","author":[{"given":"P. S.","family":"Ramesh","sequence":"first","affiliation":[{"name":"Department of Computer Science and Engineering, Vel Tech Rangarajan Dr. Sagunthala R & D Institute of Science and Technology, Chennai 600062, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"P.","family":"Srivani","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, BMS Institute of Technology and Management, Yelahanka, Bengaluru 560064, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9720-2201","authenticated-orcid":false,"given":"Miroslav","family":"Mahdal","sequence":"additional","affiliation":[{"name":"Department of Control Systems and Instrumentation, Faculty of Mechanical Engineering, VSB-Technical University of Ostrava, 17. Listopadu 2172\/15, 70800 Ostrava, Czech Republic"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1062-1578","authenticated-orcid":false,"given":"Lingala","family":"Sivaranjani","sequence":"additional","affiliation":[{"name":"School of Computing, Mohan Babu University, Tirupati 517102, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shafiqul","family":"Abidin","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Aligarh Muslim University, Aligarh 202001, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shivakumar","family":"Kagi","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Sharnbasva University, Kalaburagi 585105, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2349-3701","authenticated-orcid":false,"given":"Muniyandy","family":"Elangovan","sequence":"additional","affiliation":[{"name":"Department of Biosciences, Saveetha School of Engineering, Saveetha Nagar, Thandalam 602105, India"},{"name":"Department of R&D, Bond Marine Consultancy, London EC1V 2NX, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,7,24]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"18855","DOI":"10.1109\/TITS.2022.3161977","article-title":"Disparity-Based Multiscale Fusion Network for Transportation Detection","volume":"23","author":"Chen","year":"2022","journal-title":"IEEE Trans. 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