NDLI: Enhanced First-Fit Decreasing Algorithm for Energy-Aware Job Scheduling in Cloud

Content Provider	IEEE Xplore Digital Library
Author	Alahmadi, A. Alnowiser, A. Zhu, M.M. Che, D. Ghodous, P.
Copyright Year	2014
Description	Author affiliation: Dept. of Comput. Sci., Univ. Lyon 1, Villeurbanne, France (Ghodous, P.) \|\| Dept. of Comput. Sci., Southern Illinois Univ., Carbondale, IL, USA (Alahmadi, A.; Alnowiser, A.; Zhu, M.M.; Che, D.)
Abstract	With the emerging of many data centers around the globe, heavy loads of large-scale commercial and scientific applications executed in the cloud call for efficient cloud resource management strategies to save energy without compromising the performance and system throughput. According to the statistics from the Data Centre Dynamic (DCD) organization, the expected energy consumption by computer servers would increase by 19% in 2013 compared with the previous year. Such trend may continue for many years. Moreover, the estimated energy consumption of computers in the U.S. was about 2% out of the total electricity consumption in 2010, which makes IT industry the second pollution contributor after aviation. In this paper, a novel approach for scheduling, sharing and migrating Virtual Machines (VMs) for a bag of cloud tasks is designed and developed to reduce energy consumption with guaranteed certain execution time and high system throughput. This approach is derived from an Enhanced First Fit Decreasing (EFFD) algorithm combined with our VM reuse strategy. Furthermore, virtual machine migration method is introduced to dynamically monitor the cloud situation for necessary migration. Our simulation results using Cloud Report show that EFFD with our VM reuse strategy gains higher resource utilization rate and lower energy consumption than Greedy, Round Robin (RR) and FDD without VM reuse.
Starting Page	69
Ending Page	74
File Size	273485
Page Count	6
File Format	PDF
ISBN	9781479930104
DOI	10.1109/CSCI.2014.97
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-03-10
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Energy consumption Power demand Coud Computing VM scheduling Virtual machining Scheduling Resource management Servers
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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