DocumentCode
2183046
Title
PACO: A Period ACO Based Scheduling Algorithm in Cloud Computing
Author
Weifeng Sun ; Ning Zhang ; Haotian Wang ; Wenjuan Yin ; Tie Qiu
Author_Institution
Sch. of Software Technol., Dalian Univ. of Technol., Dalian, China
fYear
2013
fDate
16-19 Dec. 2013
Firstpage
482
Lastpage
486
Abstract
Tasks scheduling problem in cloud computing is NP-hard, and it is difficult to attain an optimal solution, so we can use intelligent optimization algorithms to approximate the optimal solution, such as ant colony optimization algorithm. In order to solve the task scheduling problem in cloud computing, a period ACO_based scheduling algorithm (PACO) has been proposed in this paper. PACO uses ant colony optimization algorithm in cloud computing, with the first proposed scheduling period strategy and the improvement of pheromone intensity update strategy. The experiments results show that, PACO has a good performance both in makespan and load balance of the whole cloud cluster.
Keywords
ant colony optimisation; cloud computing; computational complexity; scheduling; NP-hard problem; PACO; ant colony optimization algorithm; cloud cluster; cloud computing; intelligent optimization algorithms; period ACO based scheduling algorithm; tasks scheduling problem; Algorithm design and analysis; Cloud computing; Clustering algorithms; Heuristic algorithms; Scheduling; Scheduling algorithms; ant colony algorithm; cloud computing; scheduling period; task scheduling;
fLanguage
English
Publisher
ieee
Conference_Titel
Cloud Computing and Big Data (CloudCom-Asia), 2013 International Conference on
Conference_Location
Fuzhou
Print_ISBN
978-1-4799-2829-3
Type
conf
DOI
10.1109/CLOUDCOM-ASIA.2013.85
Filename
6821036
Link To Document