 |
|
|
|
 |
 |
 |
|
 |
|
 |
|
|
| 谭一鸣,曾国荪,王伟.随机任务在云计算平台中能耗的优化管理方法.软件学报,2012,23(2):266-278 |
| 随机任务在云计算平台中能耗的优化管理方法 |
| Policy of Energy Optimal Management for Cloud Computing Platform with Stochastic Tasks |
| 投稿时间：2011-07-15 修订日期：2011-09-06 |
| DOI：10.3724/SP.J.1001.2012.04143 |
| 中文关键词: 绿色云计算 随机任务 能耗管理 任务调度 排队论 |
| 英文关键词:green cloud computing stochastic task energy management task scheduling queueing theory |
| 基金项目:国家自然科学基金(61103068); 国家高技术研究发展计划(863)(2009AA012201); NSFC-微软亚洲研究院联合资助项目(60970155) |
|
| 摘要点击次数: 6791 |
| 全文下载次数: 6319 |
| 中文摘要: |
| 针对云计算系统在运行过程中由于计算节点空闲而产生大量空闲能耗,以及由于不匹配任务调度而产生大量“奢侈”能耗的能耗浪费问题,提出一种通过任务调度方式的能耗优化管理方法.首先,用排队模型对云计算系统进行建模,分析云计算系统的平均响应时间和平均功率,建立云计算系统的能耗模型.然后提出基于大服务强度和小执行能耗的任务调度策略,分别针对空闲能耗和“奢侈”能耗进行优化控制.基于该调度策略,设计满足性能约束的最小期望执行能耗调度算法ME3PC(minimum expectation execution energy with performance constraints).实验结果表明,该算法在保证执行性能的前提下,可大幅度降低云计算系统的能耗开销. |
| 英文摘要: |
| In the running process of cloud computing system, the idle compute nodes will generate a large amount of idle energy consumption. Furthermore, the unmatching task scheduling strategy will also cause a great waste of energy consumption. This paper presents a policy of energy optimal management for cloud computing system based on task scheduling strategy. First, use queueing system to model the cloud computing system for analyzing the mean response time, mean power consumption of cloud computing system, and constructing the energy consumption model of cloud computing system. In order to reduce waste of energy, a high service utilization task scheduling and a low execution energy task scheduling strategy are propsed, which are used to reduce idle energy and “luxury” energy respectively. Based on the idea of the strategies, an algorithm is designed which is called minimum expectation execution energy with performance constraints (ME3PC). Repeated experiments show that this energy management strategy can reduce the energy consumption considerably while meeting performance constraints. |
|
HTML 下载PDF全文 查看/发表评论 下载PDF阅读器 |
|
|
|
|
|
|
 |
|
|
|
|
 |
|
 |
|
 |
|
