A learning-based approach for fault tolerance on grid resources scheduling

While Grid environment has developed increasingly, unfortunately the importance of fault tolerance has not been remarkable in Grid resource management. On the other hand, the cost of computing by grid is important because grid is an economy-based system. Most organizations intend to spend little on their own computations by grid. Therefore, using a better approach to resource scheduling to avoid fault is necessary. This paper presents a new approach on fault tolerance mechanisms for the resource scheduling on grid by using Case-Based Reasoning technique in a local fashion. This approach applies a specific structure in order to prepare fault tolerance between exécuter nodes to retain system in a safe state with minimum data transferring. Certainly, this algorithm increases fault tolerant confidence therefore, performance of grid will be high.