Joint power optimization through VM placement and flow scheduling in data centers

Dawei Li, Jie Wu, Zhiyong Liu, Fa Zhang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

Two important components that consume the majority of IT power in data centers are the servers and the Data Center Network (DCN). Existing works fail to fully utilize power management techniques on the servers and in the DCN at the same time. In this paper, we jointly consider VM placement on servers with scalable frequencies and flow scheduling in the DCN, to minimize the overall system's power consumption. Due to the convex relation between a server's power consumption and its operating frequency, we prove that, given the number of servers to be used, computation workloads should be allocated to severs in a balanced way, to minimize the power consumption on servers. To reduce the power consumption of the DCN, we further consider the flow requirements among the VMs during VM allocation and assignment. Also, after VM placement, flow consolidation is conducted to reduce the number of active switches and ports. We notice that, choosing the minimum number of servers to accommodate the VMs may result in high power consumption on servers, due to servers' increased operating frequencies. Choosing the optimal number of servers purely based on servers' power consumption leads to reduced power consumption on servers, but may increase power consumption of the DCN. We propose to choose the optimal number of servers to be used, based on the overall system's power consumption. Simulations show that, our joint power optimization method helps to reduce the overall power consumption significantly, and outperforms various existing state-of-the-art methods in terms of reducing the overall system's power consumption.

Original languageEnglish
Title of host publication2014 IEEE 33rd International Performance Computing and Communications Conference, IPCCC 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479975754
DOIs
StatePublished - 20 Jan 2015
Event33rd IEEE International Performance Computing and Communications Conference, IPCCC 2014 - Austin, United States
Duration: 5 Dec 20147 Dec 2014

Publication series

Name2014 IEEE 33rd International Performance Computing and Communications Conference, IPCCC 2014
Volume2014-January

Other

Other33rd IEEE International Performance Computing and Communications Conference, IPCCC 2014
Country/TerritoryUnited States
CityAustin
Period5/12/147/12/14

Keywords

  • Data centers
  • data center networks
  • flow scheduling
  • joint power optimization
  • virtual machine (VM) placement

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