A Survey on Resource Scheduling in Cloud Computing: Issues and Challenges

Abstract

Resource scheduling in cloud is a challenging job and the scheduling of appropriate resources to cloud workloads depends on the QoS requirements of cloud applications. In cloud environment, heterogeneity, uncertainty and dispersion of resources encounters problems of allocation of resources, which cannot be addressed with existing resource allocation policies. Researchers still face troubles to select the efficient and appropriate resource scheduling algorithm for a specific workload from the existing literature of resource scheduling algorithms. This research depicts a broad methodical literature analysis of resource management in the area of cloud in general and cloud resource scheduling in specific. In this survey, standard methodical literature analysis technique is used based on a complete collection of 110 research papers out of large collection of 1206 research papers published in 19 foremost workshops, symposiums and conferences and 11 prominent journals. The current status of resource scheduling in cloud computing is distributed into various categories. Methodical analysis of resource scheduling in cloud computing is presented, resource scheduling algorithms and management, its types and benefits with tools, resource scheduling aspects and resource distribution policies are described. The literature concerning to thirteen types of resource scheduling algorithms has also been stated. Further, eight types of resource distribution policies are described. Methodical analysis of this research work will help researchers to find the important characteristics of resource scheduling algorithms and also will help to select most suitable algorithm for scheduling a specific workload. Future research directions have also been suggested in this research work.

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Correspondence to Sukhpal Singh.

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Singh, S., Chana, I. A Survey on Resource Scheduling in Cloud Computing: Issues and Challenges. J Grid Computing 14, 217–264 (2016). https://doi.org/10.1007/s10723-015-9359-2

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Keywords

  • Resource scheduling algorithms
  • Resource management
  • Resource distribution policies
  • Cloud computing
  • Resource scheduling tools
  • Cloud workloads
  • Resource scheduling aspects
  • Resource provisioning
  • Cloud resource scheduling