期刊
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
卷 59, 期 -, 页码 14-27出版社
ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.jnca.2015.05.001
关键词
Energy aware scheduling; Data-intensive application; SLA violation rate; Data correlation
类别
资金
- National Natural Science Foundation of China [61202415, 61272509, 61402332]
- Natural Science Foundation of Tianjin University of Science and Technology [20130124]
- grants of the talent startup project - Tianjin University of Science and Technology [20140502]
- NSF of Tianjin [15JCQNJC00700]
Maximizing energy efficiency while ensuring the user's Service-Level Agreement (SLA) is very important for the purpose of environmental protection and profit maximization for the cloud service providers. In this paper, an energy and deadline aware task scheduling method for data-intensive applications is proposed. In this method, first, the datasets and tasks are modeled as a binary tree by a data correlation clustering algorithm, in which both the data correlations generated from the initial datasets and that from the intermediate datasets have been considered. Hence, the amount of global data transmission can be reduced greatly, which are beneficial to the reduction of SLA violation rate. Second, a Tree-to-Tree task scheduling approach based on the calculation of Task Requirement Degree (TRD) is proposed, which can improve energy efficiency of the whole cloud system by reducing the number of active machines, decreasing the global time consumption on data transmission, and optimizing the utilization of its computing resources and network bandwidth. Experiment results show that the power consumption of the cloud system can be reduced efficiently while maintaining a low-level SLA violation rate. (C) 2015 Elsevier Ltd. All rights reserved.
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