Task balanced workflow scheduling technique considering task processing rate in spot market

Daeyong Jung, Jongbeom Lim, Joonmin Gil, Eunyoung Lee, Heonchang Yu

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)


Recently, the cloud computing is a computing paradigm that constitutes an advanced computing environment that evolved from the distributed computing. And the cloud computing provides acquired computing resources in a pay-as-you-go manner. For example, Amazon EC2 offers the Infrastructure-as-a-Service (IaaS) instances in three different ways with different price, reliability, and various performances of instances. Our study is based on the environment using spot instances. Spot instances can significantly decrease costs compared to reserved and on-demand instances. However, spot instances give a more unreliable environment than other instances. In this paper, we propose the workflow scheduling scheme that reduces the out-of-bid situation. Consequently, the total task completion time is decreased. The simulation results reveal that, compared to various instance types, our scheme achieves performance improvements in terms of an average combined metric of 12.76% over workflow scheme without considering the processing rate. However, the cost in our scheme is higher than an instance with low performance and is lower than an instance with high performance.

Original languageEnglish
Article number237960
JournalJournal of Applied Mathematics
Publication statusPublished - 2014

ASJC Scopus subject areas

  • Applied Mathematics


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