Efficient Resource Management and Scheduling in Cloud Computing: A Survey of Methods and Emerging Challenges
DOI:
https://doi.org/10.63282/3050-9246.IJETCSIT-V4I3P112Keywords:
Cloud Computing, Resource Management, scheduling algorithms, Energy Efficiency, Resource AllocationAbstract
Cloud computing has changed the way modern IT infrastructure works by letting users access computer resources in a way that is scalable, flexible, and on-demand. But making sure that these resources are managed and scheduled well is still important for performance, cost-effectiveness, and energy economy. This essay covers all the different ways to handle resources and make schedules in cloud computing, including old-fashioned methods, smart algorithms, and environmentally friendly ways of doing things. It talks about different ways to schedule and assign resources, such as heuristic, meta-heuristic, machine learning-based, and control-theory-driven models. A lot of attention is paid to managing resources in data centers in a way that saves energy, managing workloads, and optimizing virtual machines in real time. Furthermore, the study identifies key challenges such as workload heterogeneity, elasticity, cost minimization, SLA compliance, and energy-efficient scheduling. The paper also explores architecture models, taxonomy of scheduling layers, and the implications of big data in cloud operations. By consolidating current research and highlighting emerging issues, this paper aims to serve as a valuable reference for researchers and practitioners working toward optimized and sustainable cloud resource management solutions. The insights presented are intended to support the development of scalable frameworks that ensure high availability, reduced latency, and enhanced quality of service in diverse cloud environments
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