A survey and taxonomy on workload scheduling and resource provisioning in hybrid clouds
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A survey and taxonomy on workload scheduling and resource provisioning in hybrid clouds Bo Wang1
•
Changhai Wang1 • Ying Song2,3 • Jie Cao1 • Xiao Cui1 • Ling Zhang1
Received: 25 February 2019 / Revised: 1 November 2019 / Accepted: 6 January 2020 Ó Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract Hybrid cloud is a cost-efficient way to address the problem of insufficient resources for meeting the peak demand of its users for a service provider, which elastically scales up or down the cloud capability based on demand by combining local infrastructures and one or more public clouds. While, the combination introduces new challenges that must necessarily be addressed before adoption. To address these new challenges for improving the resource efficiency in hybrid clouds, much work tried to solve the decision problem of workload scheduling, resource provisioning, or both, where workload scheduling answers how to efficiently map workloads to available resources, and resource provisioning addresses how to optimally provision resources based on demand. In this article, we proposed a comprehensive taxonomy of workload scheduling and resource provisioning in hybrid cloud environments to investigate and classify 146 related research articles. Based on the investigation, we summarized the challenges which have not been addressed by these researches, and discussed future directions and trends in the area. Keywords Cloud computing Hybrid cloud Resource provisioning Workload scheduling
1 Introduction Cloud computing has received increasing attention in both research and business for about one decade due as it provides a great deal of benefits, e.g., elastic resource provisioning, pay-for-use, economies of scale, high reliability, dynamic customization, etc. [175]. But although resources appear to be infinite to users, a cloud has limited resources in the real world. Thus a cloud should have enough resources for satisfying the peak demand of its users’
& Bo Wang [email protected] Changhai Wang [email protected] 1
Software Engineering College, Zhengzhou University of Light Industry, Zhengzhou 450002, China
2
Beijing Advanced Innovation Center for Materials Genome Engineering, Beijing Information Science and Technology University, Beijing 100101, China
3
Beijing Key Laboratory of Internet Culture and Digital Dissemination, Beijing Information Science and Technology University, Beijing 100101, China
requests to satisfy all Quality of Service (QoS) requirements of users for its reputation [45]. When there are insufficient resources for a local cloud meeting the peak demand of its users, three methods can be exploited. The first one is to reject some unimportant requests, e.g., cheap requests, to make room for important requests whose rejections cost much more [106]. While this method would reduce the cloud provider’s reputation [45], and may further result in the loss of potential users. Second, the cloud provider increases infrastructures enou
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