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Scheduling Strategies for Business Process Applications in Cloud Environments

Scheduling Strategies for Business Process Applications in Cloud Environments

Kahina Bessai, Samir Youcef, Ammar Oulamara, Claude Godart, Selmin Nurcan
Copyright: © 2013 |Volume: 5 |Issue: 4 |Pages: 14
ISSN: 1938-0259|EISSN: 1938-0267|EISBN13: 9781466635715|DOI: 10.4018/ijghpc.2013100105
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MLA

Bessai, Kahina, et al. "Scheduling Strategies for Business Process Applications in Cloud Environments." IJGHPC vol.5, no.4 2013: pp.65-78. http://doi.org/10.4018/ijghpc.2013100105

APA

Bessai, K., Youcef, S., Oulamara, A., Godart, C., & Nurcan, S. (2013). Scheduling Strategies for Business Process Applications in Cloud Environments. International Journal of Grid and High Performance Computing (IJGHPC), 5(4), 65-78. http://doi.org/10.4018/ijghpc.2013100105

Chicago

Bessai, Kahina, et al. "Scheduling Strategies for Business Process Applications in Cloud Environments," International Journal of Grid and High Performance Computing (IJGHPC) 5, no.4: 65-78. http://doi.org/10.4018/ijghpc.2013100105

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Abstract

The Cloud computing paradigm is adopted for its several advantages like reduction of cost incurred when using a set of resources. However, despite the many proven benefits of using a Cloud infrastructure to run business processes, it is still faced with a major problem that can compromise its success: the lack of guidance for choosing between multiple offerings. Moreover, when running business processes it is difficult to automate all tasks and several objectives often conflicting must be taken into account. For this, the authors propose a set of scheduling strategies for business processes in Cloud contexts. More precisely, the authors propose three bi-criteria complementary approaches for scheduling business processes on distributed Cloud resources while taking into account its elastic computing characteristic that allows users to allocate and release compute resources (virtual machines) on-demand and its business model based on pay as you go. Therefore, it is reasonable to assume that the number of virtual machine is infinite while the number of human resources is finite. Experiment results demonstrate that the proposed approaches present good performances.

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