期刊
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
卷 94, 期 -, 页码 363-385出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.rser.2018.06.005
关键词
Datacenters; Resource management; Server consolidation; Dynamic capacity planing; VM migration; Energy efficiency
资金
- Department of Computer Science, University of Surrey, UK
- Abdul Wali Khan University Mardan, Pakistan
Computing systems have been focused on performance improvements, driven by the demand of user applications in past few decades, particularly from 1990 to 2010. However, due to their ever-increasing energy demand which causes large energy bills and CO2 emissions, over the past six years the focus has shifted towards energy-performance aware. The average energy consumption of servers is increasing continuously; and several researchers suggest, if this trend continues further, the cost of energy consumed by a server during its lifetime will exceed the hardware costs. The energy consumption problem is even greater for large-scale infrastructures, such as clusters, grids and clouds, which consist of several thousand heterogeneous servers. Efforts are continuously made to minimize the energy consumption of these systems, but the interest of people in computational services and popularity of smart devices make it a difficult task. In this paper, we discuss the energy consumption of ICT equipment, and present a taxonomy of energy and performance efficient techniques for large computing systems covering clusters, grids and clouds (datacenters). We discuss both energy and performance efficiency, which makes this survey different from those already published in the literature. Key research papers are surveyed and mapped onto taxonomies to characterise and identify outstanding and key issues for further research. We discuss several state-of-the-art resource management techniques, reported in the literature, that claim significant improvement in the energy efficiency and performance of ICT equipment and large-scale computing systems such as datacenters, and identify a few open challenges.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据