Copyright © 2004 Elsevier B.V. All rights reserved.
Grid load balancing using intelligent agents
Available online 28 October 2004.
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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.
Keywords: Load balancing; Grid computing; Intelligent agents; Genetic algorithm; Service discovery
Article Outline
- 1. Introduction
- 2. Grid agents
- 2.1. Agent structure
- 2.2. Agent hierarchy
- 2.3. Performance prediction
- 3. Local grid load balancing
- 4. Global grid load balancing
- 5. Performance evaluation
- 5.1. Performance metrics
- 5.1.1. Total application execution time
- 5.1.2. Average advance time of application execution completion
- 5.1.3. Average resource utilisation rate
- 5.1.4. Load-balancing level
- 5.2. Experimental design
- 5.3. Experimental results
- 5.3.1. Experiment 1
- 5.3.2. Experiment 2
- 5.3.3. Experiment 3
- 5.3.4. Application execution
- 5.3.5. Resource utilisation
- 5.3.6. Load balancing
- 5.4. Agent performance
- 6. Related work
- 7. Conclusions
- References
- Vitae







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