Ant Colony Optimization Algorithm to Dynamic Energy Management in Cloud Data Center

Ant Colony Optimization Algorithm to Dynamic Energy Management in Cloud Data Center
复制标题

云数据中心动态能源管理的蚁群优化算法

DOI:
10.1155/2017/4810514
复制
发表时间:
2017-12
影响因子:
--
通讯作者:
Gao Qian
Gao Qian
中科院分区:
工程技术4区
文献类型:
--
作者:
Pang Shanchen;Zhang Weiguang;Ma Tongmao;Gao Qian

文献摘要

参考文献

被引文献

相似文献

随着云计算数据中心的广泛部署,功耗问题日益突出。研究了云数据中心中追求能源效率的动态能源管理问题。具体来说,构建了一个云数据中心的动态能源管理系统模型,该系统由DVS管理模块、负载均衡模块和任务调度模块组成。在任务调度模块中,利用随机Petri网对调度过程进行分析,提出了一种面向任务的资源分配方法(LET-ACO),通过对任务的调度来优化系统的运行时间和能耗。仿真研究证实了所提出的系统模型的有效性。仿真结果还表明,与蚁群算法、Min-Min算法和RR算法相比,LET-ACO算法在满足性能约束的前提下,分别节省了28%、31%和40%的能耗。
With the wide deployment of cloud computing data centers, the problems of power consumption have become increasingly prominent. The dynamic energy management problem in pursuit of energy-efficiency in cloud data centers is investigated. Specifically, a dynamic energy management system model for cloud data centers is built, and this system is composed of DVS Management Module, Load Balancing Module, and Task Scheduling Module. According to Task Scheduling Module, the scheduling process is analyzed by Stochastic Petri Net, and a task-oriented resource allocation method (LET-ACO) is proposed, which optimizes the running time of the system and the energy consumption by scheduling tasks. Simulation studies confirm the effectiveness of the proposed system model. And the simulation results also show that, compared to ACO, Min-Min, and RR scheduling strategy, the proposed LET-ACO method can save up to 28%, 31%, and 40% energy consumption while meeting performance constraints.
DOI: 10.1016/j.compeleceng.2013.11.023
发表时间: 2014
期刊: Comput. Electr. Eng.
影响因子: --
作者:
Elina Pacini;C. Mateos;C. Garino
通讯作者: Elina Pacini;C. Mateos;C. Garino
DOI: 10.1155/1999/386856
发表时间: 1999-08
期刊: Sci. Program.
影响因子: --
作者:
P. Dinda
通讯作者: P. Dinda
DOI: 10.1016/j.jnca.2016.11.026
发表时间: 2017-02
期刊: J. Netw. Comput. Appl.
影响因子: --
作者:
Chao-Tung Yang;Jung-Chun Liu;Shuo-Tsung Chen;K. Huang
通讯作者: Chao-Tung Yang;Jung-Chun Liu;Shuo-Tsung Chen;K. Huang
DOI: 10.1080/18756891.2013.864479
发表时间: 2014-09
期刊: Int. J. Comput. Intell. Syst.
影响因子: --
作者:
Guoyuan Lin;Yuyu Bie;Min Lei;K. Zheng
通讯作者: Guoyuan Lin;Yuyu Bie;Min Lei;K. Zheng
DOI: 10.1109/jsee.2014.00053
发表时间: 2014-07
影响因子: 2.1
作者:
Gangjun Tan;Tao Song;Zhihua Chen
通讯作者: Gangjun Tan;Tao Song;Zhihua Chen