SLA-Aware Resource Scaling for Energy Efficiency

Eidah J. Alzahrani, Zahir Tari, Panlop Zeephongsekul, Young Choon Lee, Deafallah Alsadie, Albert Y. Zomaya

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

1 Citation (Scopus)

Abstract

Cloud data centers (CDCs) with abundant resource capacities have prevailed in the past decade. However, these CDCs often struggle to efficiently deal with resource provisioning in terms of performance and energy efficiency. In this paper, we present Energy-Based Auto Scaling (EBAS) as a new resource auto-scaling approach - that takes into account Service Level Agreement (SLA) - for CDCs. EBAS proactively scales resources at the CPU core level in terms of both the number and frequency of cores. It incorporates the dynamic voltage and frequency scaling (DVFS) technique to dynamically adjust CPU frequencies. The proactive decisions on resource scaling are enabled primarily by the CPU usage prediction model and the workload consolidation model of EBAS. The experimental results show that EBAS can save energy on average by 14% compared with the Linux governor. In particular, EBAS contributes to enhancing DVFS by making it aware of SLA conditions, which leads to savings of computing power and in turn energy.

Original languageEnglish
Title of host publicationProceedings - 18th IEEE International Conference on High Performance Computing and Communications, 14th IEEE International Conference on Smart City and 2nd IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2016
EditorsJinjun Chen, Laurence T. Yang
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages852-859
Number of pages8
ISBN (Electronic)9781509042968
DOIs
Publication statusPublished - Dec 2016
Event18th IEEE International Conference on High Performance Computing and Communications, 14th IEEE International Conference on Smart City and 2nd IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2016 - Sydney, Australia
Duration: 12 Dec 201614 Dec 2016

Other

Other18th IEEE International Conference on High Performance Computing and Communications, 14th IEEE International Conference on Smart City and 2nd IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2016
CountryAustralia
CitySydney
Period12/12/1614/12/16

Keywords

  • Auto-Scaling
  • Cloud Data Centers
  • Docker Containers
  • Energy Efficiency
  • Resource Provisioning

Fingerprint Dive into the research topics of 'SLA-Aware Resource Scaling for Energy Efficiency'. Together they form a unique fingerprint.

Cite this