{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T20:24:00Z","timestamp":1761164640904,"version":"build-2065373602"},"reference-count":8,"publisher":"Wiley","issue":"5","license":[{"start":{"date-parts":[[2025,7,14]],"date-time":"2025-07-14T00:00:00Z","timestamp":1752451200000},"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":[[2025,9]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>To meet the increasing demands of the modern networks, the dynamic resource allocation (DRA), improved Scalability and intelligent traffic management were made possible by the virtualization of the Cloud\u2010native 5G Core Network (5GC). 5GC successfully manages the various network services using cloud\u2010native principles, which could increase 5GC's potential in terms of automation, flexibility, and efficiency. Current 5GC applications primarily face three challenges: poor traffic management tactics, limited scalability in heavy traffic loads, and inefficient resource utilization (RU). Conventional virtualization techniques do not achieve dynamic response to changing network needs. Those traditional approaches may lead to higher latency and performance constraints. We suggest the Cloud\u2010Native Adaptive 5G Core (CA5GC) Framework, which combines AI\u2010driven traffic management, microservice\u2010based architectures, and containerized network operations to address these problems. To maximize resource usage, guarantee scalability, and improve intelligent traffic handling, the framework makes use of dynamic network slicing, Kubernetes\u2010based orchestration, and machine learning\u2010powered predictive traffic analysis. The proposed CA5GC framework facilitates real\u2010time adaptation of 5GC resources, ensuring optimal network performance even during peak loads. By integrating intelligent traffic classification and automated orchestration, CA5GC enhances network efficiency and reduces operational costs for service providers. Significant improvements in resource efficiency, reduced network congestion, and enhanced service quality are attained by the potential of CA5GC. The results are encouraging, with 96.35% resource utilization and 95.27% service quality achieved. These metrics reflect the framework's effectiveness in optimizing performance in cloud\u2010native 5G environments.<\/jats:p>","DOI":"10.1002\/itl2.70076","type":"journal-article","created":{"date-parts":[[2025,7,14]],"date-time":"2025-07-14T14:31:57Z","timestamp":1752503517000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Cloud\u2010Native\n                    <scp>5G<\/scp>\n                    Core Network Virtualization, Scalability, and Intelligent Traffic Management Applications"],"prefix":"10.1002","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-7448-5966","authenticated-orcid":false,"given":"Shangdong","family":"Li","sequence":"first","affiliation":[{"name":"Chongqing University of International Business and Economics  Hechuan Chongqing China"}]}],"member":"311","published-online":{"date-parts":[[2025,7,14]]},"reference":[{"key":"e_1_2_8_2_1","doi-asserted-by":"publisher","DOI":"10.3390\/sym15020538"},{"key":"e_1_2_8_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/MNET.011.2000392"},{"key":"e_1_2_8_4_1","doi-asserted-by":"publisher","DOI":"10.3390\/fi16090325"},{"key":"e_1_2_8_5_1","unstructured":"R.Bruschi F.Davoli andJ. F.Pajo \u201c5G Management and Orchestration\u2013From Cloud\u2010Native to 5G\u2010Ready Applications\u201d."},{"key":"e_1_2_8_6_1","doi-asserted-by":"publisher","DOI":"10.3390\/fi13020042"},{"key":"e_1_2_8_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/EuCNC\/6GSummit51104.2021.9482425"},{"key":"e_1_2_8_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2023.3335994"},{"key":"e_1_2_8_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/NOMS54207.2022.9789856"}],"container-title":["Internet Technology Letters"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/itl2.70076","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,21]],"date-time":"2025-10-21T18:25:34Z","timestamp":1761071134000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/itl2.70076"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7,14]]},"references-count":8,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2025,9]]}},"alternative-id":["10.1002\/itl2.70076"],"URL":"https:\/\/doi.org\/10.1002\/itl2.70076","archive":["Portico"],"relation":{},"ISSN":["2476-1508","2476-1508"],"issn-type":[{"type":"print","value":"2476-1508"},{"type":"electronic","value":"2476-1508"}],"subject":[],"published":{"date-parts":[[2025,7,14]]},"assertion":[{"value":"2025-04-15","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-06-23","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-07-14","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"e70076"}}