Earticle

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

Abstract
 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

키워드

저자

• Zhoujun HU [ School of Information Science and Engineering, Central South University ]
• Zhigang HU [ School of Information Science and Engineering, Central South University ]
• Zhenhua LIU [ School of Information Science and Engineering, Central South University ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Grid and Distributed Computing

• 간기

  격월간

• pISSN

  2005-4262

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605