An Improved Ant Colony Optimization Algorithm for Improving Cloud Resource Utilization

被引：2
|
作者：
Nie Qingbin [1 ,2 ]
Li Pinghua [1 ,2 ]
机构：
[1] Chongqing Univ Posts & Telecom, Coll Mobile Commun, Chongqing, Peoples R China
[2] Sichuan Univ, Jinjinang Coll, Coll Foreign Languages, Meishan, Peoples R China
来源：
2016 INTERNATIONAL CONFERENCE ON CYBER-ENABLED DISTRIBUTED COMPUTING AND KNOWLEDGE DISCOVERY PROCEEDINGS - CYBERC 2016 | 2016年
关键词：
Cloud computing; Ant colony algorithm; utilization; task allocation;
D O I：
10.1109/CyberC.2016.66
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
In order to improve the cloud computing utilization, an Improved Ant Colony Optimization (IACO) is proposed. The proposed IACO algorithm improves pheromone factors and inspired factors innovatively based on the existent algorithms. Emulation tests are conducted in the CloudSim and the results indicate that IACO is superior to the conventional ACO and the latest IABC in task executing efficiency.
引用
收藏
页码：311 / 314
页数：4
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