A Comprehensive Energy–QoS Trade-off Modeling Framework for Heterogeneous Cloud Data Centers
DOI:
https://doi.org/10.63665/IJMEC.0807.13Keywords:
Carbon-aware computing, Cloud data centers, Energy efficiency, Energy modeling Heterogeneous systems, multi-objective optimization, Quality of Service (QoS), Resource allocation Service Level Agreement (SLA), Workload characterizationAbstract
Modern cloud data centers operate under constant pressure to deliver high performance while simultaneously reducing energy consumption and operational costs. As cloud infrastructures grow increasingly heterogeneous—comprising diverse servers, virtualization layers, and multi-tier architectures—maintaining an optimal balance between Quality of Service (QoS) and energy efficiency has become a significant challenge. Traditional resource management strategies often focus on either minimizing power usage or satisfying Service Level Agreements (SLAs), but rarely address the dynamic trade-off between these two competing objectives in an integrated manner.
This research proposes a comprehensive Energy–QoS trade-off modeling framework tailored for heterogeneous cloud data centers. The framework establishes mathematical relationships between workload characteristics, resource utilization, energy consumption, and SLA compliance. By incorporating multi-objective optimization principles, the model quantifies the impact of resource allocation decisions on both performance and power efficiency. It also introduces a penalty-based SLA violation function to capture real-world service constraints.
The expected outcome of this study is a flexible modeling foundation that enables cloud operators to make informed, adaptive decisions that balance energy savings with service reliability. The framework aims to reduce operational costs, minimize SLA violations, and enhance sustainability, thereby supporting the development of intelligent and environmentally responsible cloud computing systems.
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