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                <identifier>oai:data.mendeley.com/8pj6gb9ym2.2</identifier>
                <datestamp>2026-06-24T16:02:35Z</datestamp>
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    <dc:creator>Arifen, Radoanul</dc:creator>
    <dc:title>ClusterSense-CO: A Large-Scale Cost Optimization Dataset for Energy-Efficient CPU Cluster Operations</dc:title>
    <dc:publisher>Mendeley Data</dc:publisher>
    <dc:description>The ClusterSense-CO dataset is a large-scale dataset developed to support research on operational cost optimization and energy-efficient resource management in CPU cluster infrastructures. The dataset contains detailed information on resource utilization, power consumption, operational expenses, workload distribution, energy costs, and optimization-related performance metrics. It enables researchers to investigate cost-aware scheduling strategies, energy consumption prediction, resource provisioning techniques, and sustainable computing solutions. The dataset is suitable for developing machine learning and optimization models aimed at reducing operational costs while maintaining high system performance and resource efficiency in modern cluster computing environments.</dc:description>
    <dc:subject>Computer Science</dc:subject>
    <dc:subject>Artificial Intelligence</dc:subject>
    <dc:subject>Energy Efficiency</dc:subject>
    <dc:subject>Machine Learning</dc:subject>
    <dc:contributor id="https://orcid.org/0009-0004-1094-1397">Azad, Anisa</dc:contributor>
    <dc:contributor id="https://orcid.org/0009-0000-7117-1630">Islam, S M Meriyan </dc:contributor>
    <dc:contributor id="https://orcid.org/0009-0000-7863-7739">Saha, Aporba</dc:contributor>
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    <dc:identifier>oai:data.mendeley.com/8pj6gb9ym2.2</dc:identifier>
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