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Toward A Performing Resource Provisioning Model for Hybrid Cloud

Toward A Performing Resource Provisioning Model for Hybrid Cloud

Mohammed Rebbah, Yahya Slimani, Mohammed Debakla, Omar Smail
Copyright: © 2018 |Volume: 10 |Issue: 4 |Pages: 28
ISSN: 1938-0259|EISSN: 1938-0267|EISBN13: 9781522543398|DOI: 10.4018/IJGHPC.2018100102
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MLA

Rebbah, Mohammed, et al. "Toward A Performing Resource Provisioning Model for Hybrid Cloud." IJGHPC vol.10, no.4 2018: pp.15-42. http://doi.org/10.4018/IJGHPC.2018100102

APA

Rebbah, M., Slimani, Y., Debakla, M., & Smail, O. (2018). Toward A Performing Resource Provisioning Model for Hybrid Cloud. International Journal of Grid and High Performance Computing (IJGHPC), 10(4), 15-42. http://doi.org/10.4018/IJGHPC.2018100102

Chicago

Rebbah, Mohammed, et al. "Toward A Performing Resource Provisioning Model for Hybrid Cloud," International Journal of Grid and High Performance Computing (IJGHPC) 10, no.4: 15-42. http://doi.org/10.4018/IJGHPC.2018100102

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Abstract

This article describes how the idea of a hybrid cloud comes from the coupling of public and private clouds to more efficiently address user requirements. This article addresses the problem of resource provisioning in hybrid cloud. This article is mainly concerned about optimizing the resources provisioning task through the reduction of the tasks completion time together with minimal cost and more reliable services. Two steps are considered in the proposed model, which are brokering and scheduling. In the brokering strategy, this article formalizes the problem as a minimization problem of the completion time as the objective function, under cost and service reliability constraints. The scheduling strategy contains two phases: (i) use the balanced k-means method to classify the submitted tasks and, (ii) perform a minimum assignment using the Hungarian algorithm. The proposed model is evaluated within the simulation framework CloudSim. Experimental results demonstrate that the provisioning model significantly reduces both the response time and the slowdown of user's requests for different scheduling algorithms.

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