Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10330051 | Future Generation Computer Systems | 2005 | 15 Pages |
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.
Related Topics
Physical Sciences and Engineering
Computer Science
Computational Theory and Mathematics
Authors
Junwei Cao, Daniel P. Spooner, Stephen A. Jarvis, Graham R. Nudd,