DocumentCode :
2284466
Title :
A desired load distribution model for agent-based distributed scheduling
Author :
Li, Yangsheng ; Shen, Weiming ; Ghenniwa, Hamada
Author_Institution :
Integrated Manuf. Technol. Inst., Nat. Res. Council of Canada, London, Ont., Canada
Volume :
2
fYear :
2003
fDate :
5-8 Oct. 2003
Firstpage :
1229
Abstract :
Scheduling problems concern the allocation of limited resources over time among both parallel and sequential activities. The majority of these problems belong to the class of NP-hard. Agent-based approaches have been applied to solve difficult scheduling problems. Load balancing is usually adopted as an optimization criterion for some scheduling problems, such as resource allocation in grid computing environments. However, in many practical situations, a load balanced solution may not be feasible or attainable. To deal with this limitation, this paper presents a generic mathematical model of load distribution for resource allocation, called desired load distribution. The objective is to develop a model that can be utilized for classical resource management settings as well as a model for a many-to-many optimized market setting.
Keywords :
computational complexity; grid computing; load distribution; multi-agent systems; optimisation; resource allocation; scheduling; NP-hard problems; agent based distributed scheduling; classical resource management settings; desired load distribution model; grid computing environments; limited resource allocation; load balancing solution; many-to-many optimized market setting; optimization; scheduling problems; Computer aided manufacturing; Dynamic scheduling; Environmental economics; Grid computing; Job shop scheduling; Load management; Load modeling; Optimal scheduling; Processor scheduling; Resource management;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems, Man and Cybernetics, 2003. IEEE International Conference on
ISSN :
1062-922X
Print_ISBN :
0-7803-7952-7
Type :
conf
DOI :
10.1109/ICSMC.2003.1244579
Filename :
1244579
Link To Document :
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