Efficient Resource Allocation in Cloud Computing Environments: A Modelling Perspective
DOI:
https://doi.org/10.63876/ijtm.v2i2.124Keywords:
Cloud Computing, Resource Allocation, Workload Management, Predictive Analysis, Service-Level Agreement (SLA), Dynamic SchedulingAbstract
Efficient resource allocation remains a critical challenge in cloud computing environments due to the dynamic and heterogeneous nature of workloads and infrastructure. This paper presents a comprehensive modelling perspective to address the complexities of resource management, aiming to optimize performance while minimizing operational costs. We propose a flexible and scalable modelling framework that integrates workload characterization, predictive demand analysis, and optimization algorithms to support decision-making in resource allocation. The framework is validated through extensive simulations using real-world workload traces and benchmark scenarios. Results demonstrate significant improvements in resource utilization, energy efficiency, and service-level agreement (SLA) compliance compared to existing approaches. This study highlights the importance of model-driven strategies in enhancing the adaptability and efficiency of cloud resource management systems.
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