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78 results for “Resource Cost”
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Research ArticleOpen accessEvery word in the titleIntegrated Resource and Cost Management Scheme for Computational GridsV. K. Manavalasundaram, K. DuraiswamyProblem statement: Autonomous decision making and resource scheduling are the main objectives of market-life computational grid. Resource providers and consumers make the scheduling decisions with cost and incentive factors. The two objectives are to maximize the success rate of job execution and to minimize fairness deviation among resources. The challenge is to develop a grid-scheduling scheme that enables individual participants … …Journal of Computer Science, Vol. 8, Issue 4 · 7 Feb 2012 · 6,565 accessesView PDFCite
Research ArticleOpen accessIn the keywordsMCWDRL: Multi-Cloud Workflow Scheduling Using Deep Reinforcement Learning and Improved Workflow Segmentation for Multi-Cloud EnvironmentsS. Gowri, A. SumathiThe rapid growth of cloud computing has led to complex workflow scheduling challenges in multi-cloud environments, where efficient resource utilization, minimized makespan, and reduced costs are paramount. Traditional scheduling algorithms often struggle to adapt to the dynamic nature of cloud resources and workflows, leading to suboptimal performance. To overcome this issue, the paper proposed a novel Multi-Cloud Workflow Scheduling using … …Journal of Computer Science, Vol. 22, Issue 6 · 1 Jul 2026 · 933 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAdvanced Grasshopper Optimization Scheduling Algorithm (AGOSA) for Multi-Cloud EnvironmentsS. Gowri, A. SumathiThe multi-cloud scheduling problem refers to the challenging task of efficiently allocating and managing resources across multiple cloud environments, involving the optimization of task scheduling, resource allocation to minimize makespan, reduce resource costs, and handle the complexity of multi-cloud environments while making optimal scheduling decisions. To overcome this issue. The paper proposes a novel scheduling algorithm, the Advanced Grasshopper Optimization … …Journal of Computer Science, Vol. 21, Issue 10 · 24 Nov 2025 · 2,646 accessesView PDFCite
Research ArticleOpen accessIn the keywordsEfficient Resource Allocation and Task Scheduling in a Cloud Computing Environment using Swarm IntelligencePanuganti Hanumantha Rao, Rajakumar Subramanian, Geetha SomanThe new age of network-based computing, known as "cloud computing," is characterized by the distribution and sharing of resources over a network. These resources are available to anyone through the Internet on a pay-per-use basis. Any service that anybody uses can generate massive amounts of data. Therefore, in this scenario, there will be a significant cost associated with transferring data … …Journal of Computer Science, Vol. 20, Issue 12 · 7 Nov 2024 · 4,716 accessesView PDFCite
Research ArticleOpen accessIn the abstractHybrid Fog Resource Provisioning and Resource Allocation using MKFCM and FPANagarjun E, Dharamendra Chouhan, Dilip Kumar SMThe expansion of Internet of Things (IoT) deployments has motivated the Fog Computing (FC) paradigm, which brings mobile-edge and cloud resources together under a single model. Allocating and provisioning application tasks across such environments poses challenges due to constrained resource capabilities, heterogeneity, mobility, network hierarchy, and unpredictability. This paper addresses the need for additional computing devices that prioritize delay-sensitive applications … …Journal of Computer Science, Vol. 22, Issue 10 · 6 Oct 2026 · 462 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimized Cloud Load Balancing Using Deep Q-Learning With Inverted S-Shaped Hierarchical Reverse Superb Fairy-Wren OptimizationB. R. Yogeetha, S. P. AnandarajCloud computing offers a scalable and cost-effective platform by providing on-demand access to shared computational resources. However, effective load balancing is essential to maintain optimal performance and maximize resource utilization for ensuring even distribution of network traffic across servers, preventing overload, improving response time and enhancing the system reliability. This manuscript proposes the Deep Q-Network with Inverted S-shaped Hierarchical Reverse … …Journal of Computer Science, Vol. 22, Issue 6 · 4 Jun 2026 · 1,497 accessesView PDFCite
Technical ReportOpen accessIn the abstractFish Pond Storage Preserves Chili Puree, but Nitrogen Flow-Through Fails: Unravelling the MechanismDaimon Syukri, Rina Yenrina, Rini et al.Perishable food preservation in rural and resource-limited settings remains a significant challenge, as conventional techniques frequently depend on synthetic additives or energy-intensive processes incompatible with green chemistry principles. This study evaluated fish pond immersion as a novel, low-cost preservation method for freshly ground chili purée, investigating its efficacy with and without continuous nitrogen gas flow. Chili purée samples were packaged … …OnLine Journal of Biological Sciences, Vol. 26, Issue 1 · 30 Mar 2026 · 1,344 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Novel Time-Based Switch Migration Method (TSSM) for Load Balancing in Distributed Software-Defined NetworkingThangaraj E, Dinesh K, Prabhakaran Paulraj et al.Switch migration is predominantly used for workload balancing in distributed Software Defined Network (SDN) controllers. The Time-Sharing Switch Migration (TSSM) technique allowed the switch's responsibility to be divided based on the time duration condition of overload, which resulted in fewer overload events, fewer ping-pong controller issues, and more efficient controllers. However, it has higher controller resource utilization during TSSM working … …Journal of Computer Science, Vol. 22, Issue 3 · 6 Mar 2026 · 1,586 accessesView PDFCite
Research ArticleOpen accessIn the abstracte-Governance Practices in Nepal: Opportunities, Challenges, and Strategies from the Local LevelReg Bahadur Bhandari, Nirav Bhatta et al.This research explores the integration of digital tools for e-governance at local levels in Nepal, with a particular emphasis on the current state of digitalization and the opportunities and challenges encountered at the local level. We collected data using a qualitative research methodology, conducting semi-structured interviews and reviewing relevant documents. The findings reveal substantial advancements in digital tools for public … …Journal of Computer Science, Vol. 22, Issue 1 · 16 Feb 2026 · 2,189 accessesView PDFCite
Research ArticleOpen accessIn the abstractReinforcement Learning in Financial Services: Modelling Payment Switching as a Multi-Armed Bandit ProblemIshaya Gambo, Christopher Agbonkhese, Segun Aina et al.The ever-evolving landscape of digital payments demands continuous innovation and self-improvement. This study addresses this imperative by simulating a model for payment routing, a crucial aspect of the digital payment ecosystem. To achieve this, industry professionals were interviewed to inform the approach, emphasizing data randomization for effective data collection. Using Python, a randomized dataset is created and three Reinforcement Learning … …Journal of Computer Science, Vol. 20, Issue 11 · 12 Oct 2024 · 4,710 accessesView PDFCite