Fault Tolerance-Genetic Algorithm for Grid Task Scheduling using Check Point

One motivation of grid computing is to aggregate the power of widely distributed resources, and provide non-trivial services to users. To achieve this goal, an efficient grid fault tolerance system is an essential part of the grid. Rather than covering the whole grid fault tolerance area, this survey provides a review of the subject mainly from the perspective of check point. In this review the challenges for fault tolerance are identified. In grid environments, execution failures can occur for various reasons such as network failure, overloaded resource conditions, or non-availability of required software components. Thus, fault-tolerant systems should be able to identify and handle failures and support reliable execution in the presence of concurrency and failures. In scheduling a large number of user jobs for parallel execution on an open-resource grid system, the jobs are subject to system failures or delays caused by infected hardware, software vulnerability, and distrusted security policy. In this paper we propose a task level fault tolerance. Task-level techniques mask the effects of the execution failure of tasks. Four task level techniques are retry, alternate resource, check point and replication. Check point technique strategy achieves optimal load balance across different grid sites. These fault tolerance task level techniques can upgrade grid performance significantly at only a moderate in extra resources or scheduling delays in a risky grid computing environment.