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 Conference Paper Faculty Publications- Conference Papers 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 Lahande, Prathamesh; Kaveri, Parag; Singh, Harvinder; Sehra, Sukhjit Singh; Saini, Jatinderkumar R. Title A name given to the resource EM-ACO-ARM: An Enhanced Multiple Ant Colony Optimization Algorithm for Adaptive Resource Management in Cloud Environment Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived Procedia Computer Science;Volume;252;pp.796-805 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1016/j.procs.2025.01.040" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.procs.2025.01.040</a> <br /><br /><a href="https://www.scopus.com/pages/publications/85219187332?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/85219187332?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 Lahande P., Department of Data Science, Christ University, Lavasa (Maharashtra), Pune, India; Kaveri P., Symbiosis Institute of Computer Studies and Research, Symbiosis International (Deemed University), Pune, India; Singh H., Govt. High School, Punjab, Marauri, India; Sehra S.S., Wilfrid Laurier University, Waterloo, ON, Canada; Saini J.R., Symbiosis Institute of Computer Studies and Research, Symbiosis International (Deemed University), Pune, India Description An account of the resource Ant Colony Optimization (ACO) is an intelligent algorithm ensuring optimal resource management in cloud environments. This paper proposes an enhanced version of the ACO algorithm called Enhanced Multiple Ant Colony Optimization for Adaptive Resource Management (EM-ACO-ARM). Our approach uses multiple ant colonies undergoing several iterations of optimizations to find the optimal Virtual Machine (VM) and adapt to the convergence uncertain-ties, unlike a single ant colony in the existing ACO, which can hinder Quality of Service (QoS)-based performance parameters. We conducted experiments in a cloud-simulated environment to evaluate EM-ACO-ARM in two phases. In the first phase, we computed real-time Montage tasks using the existing ACO algorithm on VMs across ten scenarios. To ensure an unbiased comparison, the same cloud configuration was maintained in the second phase, and the same tasks were computed using the proposed EM-ACO-ARM algorithm in all ten scenarios. The experimental results demonstrate that EM-ACO-ARM improves Execution Cost and Execution Time, leading to a 14.73% increase in Resource Utilization. This ultimately improves the management of cloud resources. Additionally, a stability evaluation was conducted using regression models, and it outputted EM-ACO-ARM to provide more stability than the existing ACO algorithm. The cloud can provide better QoS with the proposed EM-ACO-ARM algorithm while abiding by Service Level Agreements. 2025 The Authors. Published by Elsevier B.V. Subject The topic of the resource Ant Colony Optimization; Cloud Computing; Enhanced Multiple Ant Colony Optimization for Adaptive Resource Management; Performance; Resource Utilization Publisher An entity responsible for making the resource available Elsevier B.V. Relation A related resource ISSN: 18770509; Language A language of the resource English Type The nature or genre of the resource Conference paper 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