{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,22]],"date-time":"2026-07-22T15:25:20Z","timestamp":1784733920886,"version":"3.55.0"},"reference-count":9,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2025,12,12]],"date-time":"2025-12-12T00:00:00Z","timestamp":1765497600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2025,12,12]],"date-time":"2025-12-12T00:00:00Z","timestamp":1765497600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Internet Technology Letters"],"published-print":{"date-parts":[[2026,1]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>As microservices and containerized architectures gain prominence, Kubernetes has become the foundation for orchestrating distributed workloads. However, its default scheduling strategy is typically static and resource\u2010centric, lacking responsiveness to changing workload patterns, inter\u2010service communication needs, or energy efficiency goals. This paper introduces AICoLoc\u2010K8s, an adaptive scheduling enhancement framework that augments Kubernetes with intelligent, real\u2010time decision\u2010making. AICoLoc\u2010K8s leverages live system metrics collected from Prometheus and a lightweight AI model to inform pod placement decisions. Integrating a custom scheduler extender, the system dynamically evaluates candidate nodes based on multiple criteria, including CPU load, memory availability, and service tier affinity. The AI model is trained to optimize pod co\u2010location, especially for workloads categorized by frontend, backend, and database roles. We implemented AICoLoc\u2010K8s on an RKE2 cluster running inside KubeVirt virtual machines and validated its behavior through controlled experiments. The framework consistently demonstrated better placement alignment with workload characteristics than the default scheduler. Although quantifiable gains like latency and energy savings are reserved for future evaluation, initial results confirm the effectiveness of this real\u2010time adaptive model.<\/jats:p>","DOI":"10.1002\/itl2.70203","type":"journal-article","created":{"date-parts":[[2025,12,12]],"date-time":"2025-12-12T17:51:54Z","timestamp":1765561914000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["<scp>AI<\/scp>\n                    \u2010Driven Adaptive Pod Co\u2010Location in Kubernetes Using Real\u2010Time Multi\u2010Objective Optimization"],"prefix":"10.1002","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-7976-9831","authenticated-orcid":false,"given":"Sudharsan","family":"Omprakash","sequence":"first","affiliation":[{"name":"Independent Researcher"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2025,12,12]]},"reference":[{"key":"e_1_2_1_10_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/2741948.2741964"},{"key":"e_1_2_1_10_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/3005745.3005750"},{"issue":"11","key":"e_1_2_1_10_4_1","first-page":"10965","article-title":"EdgePod: A Learning\u2010Based Pod Scheduling for Edge Computing","volume":"7","author":"Xu J.","year":"2020","journal-title":"IEEE Internet of Things Journal"},{"key":"e_1_2_1_10_5_1","first-page":"244","article-title":"Graph Neural Network Based Virtual Machine Placement in Cloud Computing","volume":"115","author":"Liu Z.","year":"2021","journal-title":"Future Generation Computer Systems"},{"key":"e_1_2_1_10_6_1","article-title":"QoE\u2010Aware Container Scheduling for Co\u2010Located Cloud Applications","volume":"194","author":"Carvalho J.","year":"2022","journal-title":"Journal of Network and Computer Applications"},{"key":"e_1_2_1_10_7_1","article-title":"ACE\u2010ERAP: A Proactive and Non\u2010Disruptive Approach for Container Migration in Kubernetes Clusters","volume":"114","author":"Bagheri A.","year":"2022","journal-title":"Computers & Security"},{"key":"e_1_2_1_10_8_1","volume-title":"Prank: A QoS\u2010Driven Resource Allocation Framework for Co\u2010Located DLRAs","author":"Zhu K.","year":"2023"},{"issue":"2","key":"e_1_2_1_10_9_1","article-title":"Cortex: A Kubernetes\u2010Native Co\u2010Location Framework for Edge Clusters","volume":"15","author":"Zheng H.","year":"2023","journal-title":"Future Internet"},{"key":"e_1_2_1_10_10_1","doi-asserted-by":"crossref","unstructured":"M.Golec Y.Khamayseh S. B.Melhem andA.Alwarafy \u201cLLM\u2010Driven APT Detection for 6G Wireless Networks: A Systematic Review and Taxonomy \u201d arXiv 2505.18846(2025).","DOI":"10.1109\/ACCESS.2025.3595665"}],"container-title":["Internet Technology Letters"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/itl2.70203","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/full-xml\/10.1002\/itl2.70203","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/itl2.70203","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,23]],"date-time":"2026-01-23T03:38:54Z","timestamp":1769139534000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/itl2.70203"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12,12]]},"references-count":9,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2026,1]]}},"alternative-id":["10.1002\/itl2.70203"],"URL":"https:\/\/doi.org\/10.1002\/itl2.70203","archive":["Portico"],"relation":{"has-review":[{"id-type":"doi","id":"10.1002\/ITL2.70203\/v1\/review2","asserted-by":"object"},{"id-type":"doi","id":"10.1002\/ITL2.70203\/v1\/review1","asserted-by":"object"},{"id-type":"doi","id":"10.1002\/ITL2.70203\/v2\/review1","asserted-by":"object"},{"id-type":"doi","id":"10.1002\/ITL2.70203\/v1\/decision1","asserted-by":"object"},{"id-type":"doi","id":"10.1002\/ITL2.70203\/v2\/response1","asserted-by":"object"},{"id-type":"doi","id":"10.1002\/ITL2.70203\/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":[[2025,12,12]]},"assertion":[{"value":"2025-06-25","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-11-14","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-12-12","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"e70203"}}