In this paper, we consider the problem of supporting fault tolerance foradaptiveandtime-criticalapplications in heterogeneous and unreliable grid computing environments. Our goal for this class of applications is to optimize a user-specifiedbenefit functionwhile meeting the time deadline. Our first contribution in this paper is a multi-objective optimization algorithm for scheduling the application onto the most efficient and reliable resources. In this way, the processing can achieve the maximum benefit while also maximizing thesuccess-rate, which is the probability of finishing execution without failures. However, for the cases where failures do occur, we have developed ahybrid failure recoveryscheme to ensure that the application can complete within the pre-specified time interval. Our experimental results show that our scheduling algorithm can achieve better benefit when compared to several heuristics-based greedy scheduling algorithms, while still having a negligible overhead. Benefit is further improved when we apply the hybrid failure recovery scheme, and the success-rate becomes 100%.
Cost-based Job grouping and Scheduling Algorithm for Grid computing Environments
