{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T15:11:10Z","timestamp":1772118670208,"version":"3.50.1"},"reference-count":11,"publisher":"Wiley","issue":"4","license":[{"start":{"date-parts":[[2025,5,29]],"date-time":"2025-05-29T00:00:00Z","timestamp":1748476800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Internet Technology Letters"],"published-print":{"date-parts":[[2025,7]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>Wireless Sensor Networks (WSNs) have transformed data transmission methodologies by merging with 5G technology to provide ultra\u2010reliable, low\u2010latency, and energy\u2010efficient data transfers. Nonetheless, owing to the intricacies involved in attaining dynamic network topologies, constrained resource management, and scalability, there is a want for improved routing methodologies to optimize 5G\u2010enabled wireless sensor networks. This study introduces the \u201cNadam\u2010Swarm based Adaptive Routing Protocol using Graph Equivariant Network for Seamless Data Transmission in 5G\u2010Connected Wireless Sensor Networks\u201d (NR\u2010GE\u2010BiSO) as a proficient solution for efficient data transmission. The protocol utilizes a multi\u2010tiered approach: the Nadam\u2010based Random Search Algorithm (NR\u2010SA) dynamically allocates clustering head nodes to balance the load depending on the residual energy and traffic density of the nodes inside the network. Graph Equivariant Quantum Neural Networks (GE\u2010QNN) provide a Wireless Sensor Network (WSN) structural graph to identify optimal routing pathways based on variations within the WSN, facilitating effective data delivery with minimal power consumption. The Bipolar Swarm Optimizer (BiSO) enhanced the routing process by determining the shortest, most energy\u2010efficient routes with minimal latency and energy expenditure. Simulation results validate the efficacy of NR\u2010GE\u2010BiSO, achieving metrics: 99.92% throughput and a 99.88% packet delivery ratio with 99.01% reduction of routing overhead outperforming the existing methods. The findings indicated that the protocol facilitates energy\u2010efficient, scalable, and reliable communication. By integrating 5G capabilities with advanced routing algorithms, NR\u2010GE\u2010BiSO achieves a heightened degree of wireless sensor network efficiency, enabling innovative applications in smart cities, industrial IoT, and environmental domains.<\/jats:p>","DOI":"10.1002\/itl2.70048","type":"journal-article","created":{"date-parts":[[2025,5,29]],"date-time":"2025-05-29T04:10:35Z","timestamp":1748491835000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Nadam\u2010Swarm Based Adaptive Routing Protocol Using Graph Equivariant Network for Seamless Data Transmission in\n                    <scp>5G<\/scp>\n                    \u2010Connected Wireless Sensor Networks"],"prefix":"10.1002","volume":"8","author":[{"given":"Smita","family":"Bhore","sequence":"first","affiliation":[{"name":"Symbiosis Institute of Digital and Telecom Management (SIDTM) Symbiosis International (Deemed University)  Pune Maharashtra India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8726-5284","authenticated-orcid":false,"given":"Narambunathan Arunachalam","family":"Natraj","sequence":"additional","affiliation":[{"name":"Symbiosis Institute of Digital and Telecom Management (SIDTM) Symbiosis International (Deemed University)  Pune Maharashtra India"}]},{"given":"V.","family":"Suresh","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering Dr. N.G.P. Institute of Technology  Coimbatore Tamilnadu India"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-0215-3820","authenticated-orcid":false,"given":"M. S.","family":"Mohamed Mallick","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering Vel Tech Rangarajan Dr Sagunthala R&amp;D Institute of Science and Technology  Chennai Tamilnadu India"}]},{"given":"Sunil","family":"Lavadiya","sequence":"additional","affiliation":[{"name":"Department of Information and Communication Technology Marwadi University  Rajkot Gujarat India"}]}],"member":"311","published-online":{"date-parts":[[2025,5,29]]},"reference":[{"key":"e_1_2_7_2_1","doi-asserted-by":"publisher","DOI":"10.1155\/2022\/5424356"},{"key":"e_1_2_7_3_1","doi-asserted-by":"publisher","DOI":"10.3390\/electronics11152282"},{"key":"e_1_2_7_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jnca.2022.103556"},{"key":"e_1_2_7_5_1","doi-asserted-by":"publisher","DOI":"10.1155\/2022\/8455065"},{"key":"e_1_2_7_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2022.3142082"},{"key":"e_1_2_7_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/OJCOMS.2023.3312155"},{"key":"e_1_2_7_8_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jer.2023.10.023"},{"key":"e_1_2_7_9_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11276-023-03615-y"},{"key":"e_1_2_7_10_1","doi-asserted-by":"publisher","DOI":"10.3390\/electronics12061464"},{"key":"e_1_2_7_11_1","doi-asserted-by":"crossref","unstructured":"M. A.Jahin M. A.Masud M. W.Suva M. F.Mridha andN.Dey \u201cLorentz\u2010Equivariant Quantum Graph Neural Network for High\u2010Energy Physics \u201d arXiv Preprint arXiv:2411.01641 2024.","DOI":"10.1109\/TAI.2025.3554461"},{"key":"e_1_2_7_12_1","doi-asserted-by":"publisher","DOI":"10.22266\/ijies2024.0430.31"}],"container-title":["Internet Technology Letters"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/itl2.70048","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,29]],"date-time":"2025-08-29T13:44:11Z","timestamp":1756475051000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/itl2.70048"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,5,29]]},"references-count":11,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2025,7]]}},"alternative-id":["10.1002\/itl2.70048"],"URL":"https:\/\/doi.org\/10.1002\/itl2.70048","archive":["Portico"],"relation":{"has-review":[{"id-type":"doi","id":"10.1002\/ITL2.70048\/v2\/review1","asserted-by":"object"},{"id-type":"doi","id":"10.1002\/ITL2.70048\/v1\/decision1","asserted-by":"object"},{"id-type":"doi","id":"10.1002\/ITL2.70048\/v1\/review1","asserted-by":"object"},{"id-type":"doi","id":"10.1002\/ITL2.70048\/v2\/review2","asserted-by":"object"},{"id-type":"doi","id":"10.1002\/ITL2.70048\/v1\/review2","asserted-by":"object"},{"id-type":"doi","id":"10.1002\/ITL2.70048\/v2\/response1","asserted-by":"object"},{"id-type":"doi","id":"10.1002\/ITL2.70048\/v2\/decision1","asserted-by":"object"}]},"ISSN":["2476-1508","2476-1508"],"issn-type":[{"value":"2476-1508","type":"print"},{"value":"2476-1508","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,5,29]]},"assertion":[{"value":"2025-01-02","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-05-20","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-05-29","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"e70048"}}