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Grid load balancing using intelligent agents
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Cao, Junwei, Spooner, Daniel P., Jarvis, Stephen A. and Nudd, G. R. (2005) Grid load balancing using intelligent agents. Future Generation Computer Systems, Volume 21 (Number 1). pp. 135-149. doi:10.1016/j.future.2004.09.032 ISSN 0167-739X.
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Official URL: http://dx.doi.org/10.1016/j.future.2004.09.032
Abstract
Scalable management and scheduling of dynamic grid resources requires new technologies to build the next generation intelligent grid environments. This work demonstrates that AI techniques can be utilised to achieve effective workload and resource management. A combination of intelligent agents and multi-agent approaches is applied to both local grid resource scheduling and global grid load balancing. Each agent is a representative of a local grid resource and utilises predictive application performance data with iterative heuristic algorithms to engineer local load balancing across multiple hosts. At a higher level, agents cooperate with each other to balance workload using a peer-to-peer service advertisement and discovery mechanism.
Item Type: | Journal Article | ||||||
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Subjects: | Q Science > QA Mathematics Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software |
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Divisions: | Faculty of Science, Engineering and Medicine > Science > Computer Science | ||||||
Library of Congress Subject Headings (LCSH): | Computational grids (Computer systems), Intelligent agents (Computer software) , Multiagent systems, Genetic algorithms , Genetic programming (Computer science) | ||||||
Journal or Publication Title: | Future Generation Computer Systems | ||||||
Publisher: | Elsevier Science BV | ||||||
ISSN: | 0167-739X | ||||||
Official Date: | 1 January 2005 | ||||||
Dates: |
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Volume: | Volume 21 | ||||||
Number: | Number 1 | ||||||
Number of Pages: | 15 | ||||||
Page Range: | pp. 135-149 | ||||||
DOI: | 10.1016/j.future.2004.09.032 | ||||||
Status: | Peer Reviewed | ||||||
Publication Status: | Published | ||||||
Access rights to Published version: | Open Access (Creative Commons) |
Data sourced from Thomson Reuters' Web of Knowledge
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