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Resource Scheduling for Energy-Aware Reconfigurable Internet Data Centers

Resource Scheduling for Energy-Aware Reconfigurable Internet Data Centers

Mohammad Shojafar, Nicola Cordeschi, Enzo Baccarelli
Copyright: © 2016 |Pages: 26
ISBN13: 9781522502876|ISBN10: 1522502874|EISBN13: 9781522502883
DOI: 10.4018/978-1-5225-0287-6.ch002
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MLA

Shojafar, Mohammad, et al. "Resource Scheduling for Energy-Aware Reconfigurable Internet Data Centers." Innovative Research and Applications in Next-Generation High Performance Computing, edited by Qusay F. Hassan, IGI Global, 2016, pp. 21-46. https://doi.org/10.4018/978-1-5225-0287-6.ch002

APA

Shojafar, M., Cordeschi, N., & Baccarelli, E. (2016). Resource Scheduling for Energy-Aware Reconfigurable Internet Data Centers. In Q. Hassan (Ed.), Innovative Research and Applications in Next-Generation High Performance Computing (pp. 21-46). IGI Global. https://doi.org/10.4018/978-1-5225-0287-6.ch002

Chicago

Shojafar, Mohammad, Nicola Cordeschi, and Enzo Baccarelli. "Resource Scheduling for Energy-Aware Reconfigurable Internet Data Centers." In Innovative Research and Applications in Next-Generation High Performance Computing, edited by Qusay F. Hassan, 21-46. Hershey, PA: IGI Global, 2016. https://doi.org/10.4018/978-1-5225-0287-6.ch002

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Abstract

The pervasive use of cloud computing and the resulting growing number of Internet data centers have brought forth many concerns, including electrical energy cost, energy dissipation, cooling and carbon emission. Therefore, the need for efficient workload schedulers which are capable of minimizing the consumed energy becomes increasingly important. Green computing, a new trend for high-end computing, attempts to approach this problem by delivering both high performance and reduced energy consumption. Motivated by these considerations, in this chapter, we propose a joint computation-and-communication adaptive resource-provisioning scheduler for virtualized data centers, e.g., the Internet Data Center (IDC) scheduler, which exploits the DVFS-enabled reconfiguration capability of the underlying virtualized computing/communication platform. Specifically, we present and test a dynamic resource provisioning scheduler, which adaptively controls the execution time and bandwidth usage of each input job, as well as the internal and external switching costs on per-Virtual Machine (VM) basis.

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