원문정보
초록
영어
Task scheduling in Grid environment is a challenging problem because of NP-complete nature of scheduling issue and dynamic characteristic of the environment. Not constrained by local scheduling policy of Grid site, a dynamic service evaluation method based on cloud model is presented. Then we obtain performance metrics of dynamic service. According to dynamic service evaluation, an adaptive and dynamic service clustering method is derived from PSO (Particle Swarm Optimization)-based clustering algorithm. It gathers the services with similar or same QoS (Quality of Service) into one cluster. A dynamic meta-task scheduling algorithm is proposed in light of service clustering. We conduct extensive experiments on the implemented prototype. The results show that our algorithm outperforms prior well-established algorithms in terms of time complexity and user QoS guarantee.
목차
1. Introduction
2. Related work
3. Problem definition
4. Service-clustering-based scheduling framework
5. Service performance evaluation based on cloud model
5.1. Brief introduction to cloud model
5.2. Dynamic service evaluation based on cloud model
6. QoS-oriented dynamic service-clustering
6.1. Brief introduction to PSO
6.2. PSO-based dynamic service-clustering
7. Service-clustering-based dynamic scheduling algorithm
8. Experiment and evaluation
8.1. Experiment setup
8.2. Results and analysis
9. Conclusion
References