Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Bhatt, Rahul; Mehra, Ritika; Upreti, Kamal Title A name given to the resource AN ADAPTIVE HYBRID SCHEDULING APPROACH FOR SUSTAINABLE AND RELIABLE CLOUD SERVICES Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2026 Source A related resource from which the described resource is derived International Journal of Computer Networks and Communications;Volume;18;Issue;2;pp.39-40 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.5121/ijcnc.2026.18203" target="_blank" rel="noreferrer noopener">https://doi.org/10.5121/ijcnc.2026.18203</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105035179058?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105035179058?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Bhatt R., School of Engineering &amp; Computing, Dev Bhoomi Uttarakhand University, Uttarakhand, Dehradun, India; Mehra R., School of Engineering &amp; Computing, Dev Bhoomi Uttarakhand University, Uttarakhand, Dehradun, India; Upreti K., Department of Computer Science, Christ University, Delhi NCR Campus, Ghaziabad, India Description An account of the resource The modern cloud computing systems have to plan the heterogeneous workloads and balance performance effectiveness, service availability, and sustainability. In this study, an adaptive hybrid scheduling framework is developed Adaptive Ant-guided Min-Max (AAMM) combining ant-guided optimization with dynamic Min-Min and Max-Min in deciding how to allocate cloud tasks as a multi-objective. The scheduler jointly evaluates task completion time, the likelihood of Service Level Agreement violations, energy consumption, and monetary cost within a unified scoring framework, enabling informed trade-offs among competing objectives. AAMM is assessed based on a real disaggregated Deep Learning Recommendation Model workload of 1,544 heterogeneous tasks, running on heterogeneous virtual machines. Comparative experiments are done with Min-Min, Max-Min and ACO-guided Min-Min scheduling strategies. According to experimental findings, the suggested approach has been very effective in reducing energy per task, cost per task, SLA violations are significantly lowered, and flow time stability is enhanced. Though moderate growth in the makespan is witnessed, the accompanying trade-off has created equal distribution of resources and service reliability. 2026 Academy and Industry Research Collaboration Center (AIRCC). All rights reserved. Subject The topic of the resource Adaptive scheduling; Cloud computing; Energy-efficient cloud computing, Adaptive Ant-guided MinMax (AAMM); Multi-objective optimization; SLA-aware systems; Task scheduling Publisher An entity responsible for making the resource available Academy and Industry Research Collaboration Center (AIRCC) Relation A related resource ISSN: 9752293; Language A language of the resource English Type The nature or genre of the resource Article Rights Information about rights held in and over the resource All Open Access; Gold Open Access Format The file format, physical medium, or dimensions of the resource online