Energy efficiency of thermal-aware job scheduling algorithms under various cooling models

Georgios Varsamopoulos, Ayan Banerjee, Sandeep Gupta

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

35 Scopus citations


One proposed technique to reduce energy consumption of data centers is thermal-aware job scheduling, i.e. job scheduling that relies on predictive thermal models to select among possible job schedules to minimize its energy needs. This paper investigates, using a more realistic linear cooling model, the energy savings of previously proposed thermal-aware job scheduling algorithms, which assume a less realistic model of constant cooling. The results show that the energy savings achieved are greater than the savings previously predicted. The contributions of this paper include: i) linear cooling models should be used in analysis and algorithm design, and ii) although the job scheduler must control the cooling equipment to realize most of the thermal-aware job schedule's savings, some savings can be still achieved without that control.

Original languageEnglish (US)
Title of host publicationContemporary Computing
Subtitle of host publicationSecond International Conference, IC3 2009, Noida, India, August 17-19, 2009. Proceedings
EditorsSanjay Ranka, Srinivas Aluru, Rajkumar Buyya, Y.C. Chung, Sumeet Dua, Ananth Grama, Sandeep Gupta, Rajeev Kumar, Vir Phoha
Number of pages13
StatePublished - 2009

Publication series

NameCommunications in Computer and Information Science
ISSN (Print)1865-0929

ASJC Scopus subject areas

  • Computer Science(all)
  • Mathematics(all)


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