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 Komarasamy, Dinesh; Rajavel, Rajkumar; Harimoorthy, Karthikeyan; Pitchai, Aravind Title A name given to the resource A scalable scheduling and resource management framework for cloud-native B2B applications 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 Scientific Reports;Volume;15;Issue;1;Article No.;44500; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1038/s41598-025-28149-5" target="_blank" rel="noreferrer noopener">https://doi.org/10.1038/s41598-025-28149-5</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105025748225?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105025748225?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 Komarasamy D., Department of Computer Science and Engineering, Kongu Engineering College, Perundurai, India; Rajavel R., Department of AI, ML &amp; Data Science, Christ University, Bangalore, India; Harimoorthy K., Department of Computer Science and Engineering, Christ University, Bangalore, India; Pitchai A., Department of Electrical and Computer Engineering, Mattu University, Mattu, Ethiopia Description An account of the resource In modern cloud computing environments, customers increasingly depend on on-demand resource provisioning to handle dynamic workloads. However, fluctuations in job arrival rates can result in prolonged queue times, which negatively affect overall system performance. Although existing scheduling algorithms provide efficient job management, they often fail to account for the combined impact of queue delays and the need for flexible resource provisioningparticularly in business-critical applications. In order to tackle these issues, the paper proposes a new Optimized Job Scheduling and Resource Scaling (OJSRS) algorithm designed to improve job execution efficiency and support elastic resource management in cloud environments. The OJSRS algorithm integrates two key components: Tree-based Job Scheduling (TJS) and Automated Resource Scaling and Scheduling (ARSS). The TJS component constructs a hierarchical structure that concurrently maps incoming jobs to the most suitable Virtual Machines (VMs), thereby minimizing queue delays. Meanwhile, ARSS adjusts resource allocation dynamically, increasing or decreasing capacity according to workload requirements and cloud service provider policies, enabling responsive and adaptive provisioning. Experimental results show that the OJSRS algorithm increases resource utilization by approximately 510% and accelerates job completion through proactive resource scaling. This approach provides a significant performance advantage for cloud-native business applications that require both efficiency and scalability. The Author(s) 2025. Subject The topic of the resource Automated resource scaling; Business-to-Business applications; Cloud computing; Cloud native platform; Decent work and economic growth; Job scheduling; Load balancing Publisher An entity responsible for making the resource available Nature Research Relation A related resource ISSN: 20452322; 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; Green Open Access Format The file format, physical medium, or dimensions of the resource online