A decision-based pre-emptive fair scheduling strategy to process cloud computing work-flows for sustainable enterprise management

L. D. Dhinesh Babu, Angappa Gunasekaran, P. Venkata Krishna

Research output: Contribution to journalArticlepeer-review

35 Scopus citations


In cloud computing, clients comply a policy of pay-as-you go, i.e., they only pay for the resources they use. So, the processing power of the clouds has to be optimised to reduce the cost at client's side. Using the resources optimally ensures enterprise sustainability of cloud service providers. Workflow is a set of tasks that are interdependent on each other. Scheduling these workflows is one of the most important challenges to optimally utilise the cloud resources and ensure better quality of service (QoS) to clients. Existing works on scheduling in cloud computing mainly focus on scheduling independent tasks rather than (inter)dependent tasks. In this paper, we propose a strategy to schedule dependent tasks called pre-emptive fair scheduling algorithm (PFSA). This is fair scheduling strategy also aims to ensure higher utilisation of virtual machines (VMs) by reducing the idle time and to minimize the number of times a pre-empted task is submitted to the virtual machine. In both cases, this algorithm tries to effectively reduce the overall processing time of dependent tasks at virtual machine, thus minimising the cost involved in processing of tasks. This economically viable decision-based strategy will be helpful for cloud service providers in ensuring sustainability.

Original languageEnglish (US)
Pages (from-to)409-430
Number of pages22
JournalInternational Journal of Business Information Systems
Issue number4
StatePublished - 2014

All Science Journal Classification (ASJC) codes

  • Management Information Systems
  • Information Systems and Management
  • Management of Technology and Innovation

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