VM Capacity-Aware Scheduling within Budget Constraints in IaaS Clouds

PLoS One. 2016 Aug 8;11(8):e0160456. doi: 10.1371/journal.pone.0160456. eCollection 2016.

Abstract

Recently, cloud computing has drawn significant attention from both industry and academia, bringing unprecedented changes to computing and information technology. The infrastructure-as-a-Service (IaaS) model offers new abilities such as the elastic provisioning and relinquishing of computing resources in response to workload fluctuations. However, because the demand for resources dynamically changes over time, the provisioning of resources in a way that a given budget is efficiently utilized while maintaining a sufficing performance remains a key challenge. This paper addresses the problem of task scheduling and resource provisioning for a set of tasks running on IaaS clouds; it presents novel provisioning and scheduling algorithms capable of executing tasks within a given budget, while minimizing the slowdown due to the budget constraint. Our simulation study demonstrates a substantial reduction up to 70% in the overall task slowdown rate by the proposed algorithms.

MeSH terms

  • Algorithms
  • Cloud Computing / economics*
  • Models, Theoretical
  • Workload

Grants and funding

This research was supported by the MSIP (Ministry of Science, ICT & Future Planning), Korea, under the ITRC (Information Technology Research Center) support program (IITP-2016-H8501-16-1006) supervised by the IITP (Institute for Information & communications Technology Promotion). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.