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|Title:||Workload scheduling in cloud: A comprehensive survey and future research directions|
|Citation:||Proceedings of the 7th International Conference Confluence 2017 on Cloud Computing, Data Science and Engineering, 2017, Vol., , pp.269-275|
|Abstract:||Cloud Computing handles the computation and storage needs in an efficient and cost-effective manner. One of the emerging research area in the cloud computing is scheduling of workloads. In this paper, we present a comprehensive survey on workload scheduling in cloud computing environment. In particular, we focus on summarizing the scheduling methods, type of workloads and considered QoS parameters along with the comments on each selected studies. Furthermore, we have analyzed several workload scheduling approaches to find out the recent research trends. In addition, we have highlighted possible future research directions in this research area. One of the important finding of the survey is that, most of the approaches failed in providing adaptive scheduling policies. In future, context information such as cost, energy, workload pattern, network cost, etc can be considered to make workload scheduling policies more adaptive. � 2017 IEEE.|
|Appears in Collections:||2. Conference Papers|
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