DocumentCode
2467796
Title
An Efficient Genetic Algorithm for Task Scheduling in Heterogeneous Distributed Computing Systems
Author
Daoud, Mohammad I. ; Kharma, Nawwaf
Author_Institution
Concordia Univ., Montreal
fYear
0
fDate
0-0 0
Firstpage
3258
Lastpage
3265
Abstract
Task scheduling plays an important role in the operation of distributed computing systems. Because of its importance, several task scheduling algorithms are proposed in the literature, mainly for homogeneous processors. Few scheduling algorithms are proposed for heterogeneous distributed computing systems (HeDCSs). In this paper, we present a new approach which uses a customized genetic algorithm to produce high-quality tasks schedules for HeDCSs. The performance of the new algorithm is compared to that of two leading scheduling algorithms for HeDCSs. The comparison, which is based on both randomly generated task graphs and task graphs of certain real-world numerical applications, exhibits the supremacy of the new algorithm over the older ones, in terms of schedule length, speedup and efficiency.
Keywords
distributed processing; genetic algorithms; graph theory; scheduling; task analysis; genetic algorithm; heterogeneous distributed computing systems; randomly generated task graph; task scheduling; Application software; Computer industry; Distributed computing; Dynamic scheduling; Evolutionary computation; Genetic algorithms; High-speed networks; Job shop scheduling; Processor scheduling; Scheduling algorithm;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 2006. CEC 2006. IEEE Congress on
Conference_Location
Vancouver, BC
Print_ISBN
0-7803-9487-9
Type
conf
DOI
10.1109/CEC.2006.1688723
Filename
1688723
Link To Document