Date Added: Sep 2010
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, they 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.