Metrics for effective resource management in global computing environments

Global computing uses Internet-connected PCs volunteered by their owners. These PCs are diverse, volatile, and error-prone. Sophisticated scheduling methods commonly applied in grid computing may not be sufficiently scalable and flexible for global computing environments. This paper shows that it is possible to classify global computing hosts based on simple metrics such as availability and reliability, and that it is efficient to assign tasks to such hosts accordingly. The proposed classification of workers is applied to P@H, a global computing project for protein structure prediction