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A comprehensive survey on cloud computing scheduling techniques

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Abstract

The tremendous increase in daily internet users leads to the explosion of on-demand requests over the cloud. It causes a burden in the cloud environment (diverse and complicated applications) for cloud services. The assignment of resources to the associated task varies based on the functioning of resources available across the cloud. It establishes the importance of task scheduling in cloud computing. Inadequate scheduling techniques address the issues of resource overuse and underuse (imbalance), resulting in service degradation (in the event of overuse) or cloud resource waste (in the case of underuse or underutilized). The primary idea is to eliminate an imbalance problem by employing an appropriate scheduling algorithm that may efficiently allocate jobs (of varying and complicated types) among cloud resources. The parameters which impact the activity mentioned above are resource utilization, reliability, makespan time, cost, energy consumption, availability, response time, and other critical performance indicator metrics. In order to create a productive cloud scheduling method, these matrices need to be optimized. Many state-of-the-art cloud task scheduling algorithms based on heuristic, meta-heuristic, and hybrid design have been presented and discussed in the literature as part of the study. This study presents a comprehensive assessment and classification of various scheduling systems and their benefits and drawbacks. Our detailed & comprehensive survey effort will serve as a stepping stone for new cloud computing researchers and aid in pursuing research in this direction.

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Gupta, S., Tripathi, S. A comprehensive survey on cloud computing scheduling techniques. Multimed Tools Appl 83, 53581–53634 (2024). https://doi.org/10.1007/s11042-023-17216-6

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