Title
Task scheduling with load balancing using multiple ant colonies optimization in grid computing
Abstract
Task scheduling with load balancing in grid computing aims to assign tasks to computing nodes and minimize the execution time of tasks as well as workload across all nodes. Despite of the intractability, the scheduling problem is of particular concern to both users and grid systems. In this paper, a multiple ant colonies optimization (MACO) approach is proposed for achieving task scheduling with load balancing. In the MACO approach, multiple ant colonies work together and exchange information to collectively find solutions with a two-fold objective of minimizing the execution time of tasks and the degree of imbalance of computing nodes. Experimental results show that our algorithm outperforms FCFS and ACS approaches.
Year
DOI
Venue
2010
10.1109/ICNC.2010.5582599
ICNC
Keywords
Field
DocType
optimisation,fcfs approach,scheduling,grid computing,task analysis,multiple ant colonies optimization,resource allocation,load balancing,maco approach,task scheduling,acs approach,multiple ant colony optimization,load balance,ant colony optimization,scheduling problem,ant colony,computational modeling,algorithm design and analysis
Load management,Ant colony optimization algorithms,Job shop scheduling,Grid computing,Scheduling (computing),Computer science,Load balancing (computing),Parallel computing,Resource allocation,Ant colony,Distributed computing
Conference
Volume
ISBN
Citations 
5
978-1-4244-5958-2
7
PageRank 
References 
Authors
0.55
13
4
Name
Order
Citations
PageRank
Liang Bai137936.34
Yan-Li Hu2172.55
Song-Yang Lao320621.58
Wei Ming Zhang4696.72