Energy-aware parallel task scheduling in a cluster
Autor
Wang, Lizhe
Khan, Samee U.
Chen, Dan
Kołodziej, Joanna
Ranjan, Rajiv
Xu, Cheng-Zhong
Zomaya, Albert
Opublikowane w
Future Generation Computer Systems - The International Journal of Grid Computing and eScience
Numeracja
vol. 29, iss. 7
Strony
1661-1670
Data wydania
2013
Miejsce wydania
Amsterdam
Wydawca
Elsevier Science BV
Język
angielski
ISSN
0167-739X
DOI
10.1016/j.future.2013.02.010
Słowa kluczowe
cluster computing, green computing, task scheduling
Abstrakt
Reducing energy consumption for high end computing can bring various benefits such as reducing operating costs, increasing system reliability, and environmental respect. This paper aims to develop scheduling heuristics and to present application experience for reducing power consumption of parallel tasks in a cluster with the Dynamic Voltage Frequency Scaling (DVFS) technique. In this paper, formal models are presented for precedence-constrained parallel tasks, DVFS-enabled clusters, and energy consumption. This paper studies the slack time for non-critical jobs, extends their execution time and reduces the energy consumption without increasing the task's execution time as a whole. Additionally, Green Service Level Agreement is also considered in this paper. By increasing task execution time within an affordable limit, this paper develops scheduling heuristics to reduce energy consumption of a tasks execution and discusses the relationship between energy consumption and task execution time. Models and scheduling heuristics are examined with a simulation study. Test results justify the design and implementation of proposed energy aware scheduling heuristics in the paper.
