Adaptive task scheduling strategy in cloud: when energy consumption meets performance guarantee-Reference-Cited by-同舟云学术

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Adaptive task scheduling strategy in cloud: when energy consumption meets performance guarantee

Published:2016-02-18 Issue:2 Volume:20 Page:155-173
ISSN:1386-145X
Container-title:World Wide Web
language:en
Short-container-title:World Wide Web

Author:

Shen Yao,Bao Zhifeng,Qin Xiaolin,Shen Jian

Funder

Jiangsu Innovation Program for Graduate Education

National Natural Science Foundation of China

Research Fund for the Doctoral Program of High Education of China

National High Technology Research and Development Program of China

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Hardware and Architecture,Software

Link

http://link.springer.com/content/pdf/10.1007/s11280-016-0382-4.pdf

Reference34 articles.

1. Albers, S., Fujiwara, H.: Energy-efficient algorithms. ACM Rev. 53(5), 86–96 (2010)

2. Barroso, L.A., Holzle, U.: The case for energy-proportional computing. Computer 40(12), 33–37 (2007)

3. Basilio, S.: Provisioning computational resources using virtual machines and leases. University of Chicago, USA (2010)

4. Beloglazov, A., Abawajy, J., Buyya, R.: Energy-aware resource allocation heuristics for efficient management of data centers for cloud computing. Futur. Gener. Comput. Syst. 28(5), 755–768 (2012)

5. Beloglazov, A., Buyya, R.: Optimal online deterministic algorithms and adaptive heuristics for energy and performance efficient dynamic consolidation of virtual machines in Cloud data centers. Concurr. Comput. Pract. Exp. 24(13), 1397–1420 (2012)

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