DocumentCode :
263694
Title :
An Efficient Energy Scheduling Algorithm for Workflow Tasks in Hybrids and DVFS-Enabled Cloud Environment
Author :
Zhuo Tang ; Zhenzhen Cheng ; Kenli Li ; Keqin Li
Author_Institution :
Coll. of Inf. Sci. & Eng., Hunan Univ., Changsha, China
fYear :
2014
fDate :
13-15 July 2014
Firstpage :
255
Lastpage :
261
Abstract :
The explosive growth of energy consumption in cloud centers has become a critical issue, for going against the advocated green computing, many works focus the tasks scheduling for reducing energy dissipation. In order to obtain more energy reduction as well as maintaining the quality of service by meeting the deadlines, this paper proposes a DVFS-enabled efficient energy workflow task scheduling algorithm: DEWTS. Through merging the relatively inefficient processors byreclaiming the slack time, DEWTS can take advantage of the useful slack time once again employing DVFS technique after severs merged. Based on amount of randomly generated DAGs workflows, the experimental results show that DEWTS can reduce the total power consumption with various parallel applications as well as balancing the scheduling performance.
Keywords :
cloud computing; green computing; parallel processing; processor scheduling; quality of service; DEWTS; DVFS-enabled cloud environment; DVFS-enabled efficient energy workflow task scheduling algorithm; cloud centers; energy consumption; energy dissipation reduction; energy scheduling algorithm; green computing; parallel applications; quality of service; randomly generated DAG workflows; total power consumption reduction; workflow tasks; Algorithm design and analysis; Energy consumption; Heuristic algorithms; Merging; Processor scheduling; Program processors; Schedules; cloud computing; dynamic voltage; energy scheduling; frequency scaling; heterogeneous;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Parallel Architectures, Algorithms and Programming (PAAP), 2014 Sixth International Symposium on
Conference_Location :
Beijing
ISSN :
2168-3034
Print_ISBN :
978-1-4799-3844-5
Type :
conf
DOI :
10.1109/PAAP.2014.33
Filename :
6916474
Link To Document :
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