Cloud Resource Management to Improve Energy Efficiency Based on Local Nodes Optimizations
Cloud Resource Management to Improve Energy Efficiency Based on Local Nodes Optimizations
复制标题
基于本地节点优化的云资源管理提高能源效率
DOI：
10.1016/j.procs.2016.04.179
复制
发表时间：
2016
期刊：
影响因子：
--
通讯作者：
C. Juiz
中科院分区：
文献类型：
--
作者：
Belén Bermejo;Carlos Guerrero;I. Lera;C. Juiz
云计算系统的能耗是系统架构师当前关注的问题之一。为了减少能源消耗，他们提供了贯穿数据中心地点设计的技术，以及适当管理资源的技术，同时考虑到系统的能源消耗。本文提出了一种资源分配技术，最大限度地提高系统的效率。该技术基于在两个级别上进行决策：物理机级别和整个系统级别。每个级别都确保其自身的适当性能。为了测试该技术是否符合最初的假设，开发了通过CloudSim工具进行的模拟。此外，我们比较的结果与资源分配技术的基础上充分了解系统。因此，我们得到了更好的解决方案的时间与其他技术所提出的技术。此外，我们还减少了集群内网络的使用，并获得了更高效的云系统。
The energy consumption of Cloud Computing systems is one of the current concerns of systems architects. In order to reduce the energy consumption, they have provided techniques which go through the design of locations for data centres, together with techniques for the proper management of resources, taking into account the energy consumption of the system. This paper presents a resource allocation technique that maximizes the system efficiency. This technique is based on taking decisions at two levels: physical machine level and overall system level. Each of the levels ensure its own proper performance. To test that the technique complies with the initial hypothesis, simulations through the CloudSim tool have been developed. Also, we compared the results with a resource allocation technique based on a full knowledge of the system. As a result, we obtained a better solution time with the proposed technique that the other technique. Moreover, we obtained a lesser use of intra cluster network and a more energetically efficient cloud system.
影响因子：
56.9
作者：
Michael Armbrust;A. Fox;Rean Griffith;A. Joseph;R. Katz;A. Konwinski;Gunho Lee;D. Patterson;
通讯作者：
Michael Armbrust;A. Fox;Rean Griffith;A. Joseph;R. Katz;A. Konwinski;Gunho Lee;D. Patterson;