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Abstract: Cloud computing offers scalability, reliability, and cost-effectiveness, driving its widespread adoption. However, efficient resource management remains a challenge due to virtualization and the pay-as-you-go model (CPU, memory, network, storage, etc.). This paper addresses this by analyzing various job scheduling algorithms for task allocation and execution in the cloud. We propose a set of scheduling rules that aim to minimize completion time, cost, and resource utilization while evaluating their execution time. CloudSim is employed to analyze the overall effectiveness of the proposed scheduling techniques. Furthermore, this study investigates the result of workload characteristics and application requirements on the effectiveness of different scheduling algorithms. By understanding these factors, system designers are able to make deft choices to optimize resource allocation and enhance cloud service efficiency
Snehal Kolte (Wed,) studied this question.
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