基于包簇框架的云计算能耗优化算法

doi:10.16180/j.cnki.issn1007-7820.2019.03.013

电子科技 ›› 2019, Vol. 32 ›› Issue (3): 61-66.doi: 10.16180/j.cnki.issn1007-7820.2019.03.013

基于包簇框架的云计算能耗优化算法

陆乐¹,陈世平²

^1. 上海理工大学光电信息与计算机工程学院,上海 200093
^2. 上海理工大学信息化办公室,上海 200093

收稿日期:2018-03-18 出版日期:2019-03-15 发布日期:2019-03-01
作者简介:陆乐(1993-),男,硕士研究生。研究方向:云计算。|陈世平(1964-),男,博士,教授。研究方向:计算机网络、云计算、分布式计算。
基金资助:
国家自然科学基金(61472256)

Cloud Computing Energy Consumption Optimization Algorithm Based on Package-Cluster Mapping

LU Le¹,CHEN Shiping²

^1. School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093,China
^2. Network and Information Center Office, University of Shanghai for Science and Technology, Shanghai 200093,China

Received:2018-03-18 Online:2019-03-15 Published:2019-03-01
Supported by:
National Natural Science Foundation of China(61472256)

摘要/Abstract

摘要：

文中针对以虚拟机为中心的云计算分配模式中结构复杂、分配困难等问题,采用了一种基于包簇结构的分配框架。在此基础上提出了一个有效的能耗模型,并将二进制粒子群算法进行改进,通过调节自适应的权重,提高了包簇分配算法的速度和准确性。实验表明,改进的二进制粒子群算法在收敛速度和寻优能力方面更加优于传统的二进制粒子群算法。相较于以虚拟机为中心的分配算法,基于包簇框架下的改进二进制粒子群分配算法提升了CPU使用率,有效降低了能耗,更加绿色节能。

关键词: 云计算, 包簇, 粒子群, 能耗, 资源管理, 虚拟机放置。

Abstract: Aim

ing at the problem of flat layout and complex structure in the virtual machine placement strategy, this paper adopted a virtual machine allocation framework based on package-cluster mapping to minimize the energy consumption of all physical machines. Based on this, an effective energy consumption model and an improved binary particle swarm optimization algorithm with adaptive weights were proposed to improve the speed and accuracy of package-cluster mapping framework. Experimental results showed that the improved binary particle swarm optimization algorithm was more superior to traditional binary particle swarm optimization in terms of convergence speed and optimization ability. Compared with the virtual machine allocation algorithm, the improved binary particle swarm allocation algorithm based on the clustering framework increased the CPU usage and effectively reduced energy consumption, which promoted the green energy saving.

Key words: Science and Technology, Shanghai 200093, China)

中图分类号:

TP393.2

陆乐,陈世平. 基于包簇框架的云计算能耗优化算法[J]. 电子科技, 2019, 32(3): 61-66.

LU Le,CHEN Shiping. Cloud Computing Energy Consumption Optimization Algorithm Based on Package-Cluster Mapping[J]. Electronic Science and Technology, 2019, 32(3): 61-66.

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参考文献 16

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CPU使用率	第1次实验/W	第2次实验/W	第3次实验/W
0	91.7	92.4	94.3
10%	95.5	96.7	98.5
20%	101	102	102.4
30%	101.6	101.4	103.7
40%	105.8	106.2	106.7
50%	109.4	110.7	111.1
60%	115.4	116.2	118.4
70%	120.5	122.7	121.4
80%	124.6	124.3	127.1
90%	127.4	129.8	131.4
100%	134.8	135.6	135.9

基于包簇框架的云计算能耗优化算法

Cloud Computing Energy Consumption Optimization Algorithm Based on Package-Cluster Mapping

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