IMCLA: Performance Evaluation of Integrated Multilevel Checkpointing Algorithms using Checkpointing Efficiency

Main objective of this research work is to improve the checkpoint efficiency for integrated multilevel checkpointing algorithms (IMLCA) and prevent checkpointing from becoming the bottleneck of cloud data centers. In order to find an efficient checkpoint interval, checkpointing overheads has also considered in this paper. Traditional checkpointing methods stores persistently snapshots of the present job state and use them for resuming the execution at a later time. The attention of this research is strategies for deciding when and whether a checkpoint should be taken and evaluating them in regard to minimizing the induced monetary costs. By varying rerun time of checkpoints performance comparisons are which will be used to evaluate optimal checkpoint interval. The purposed fail-over strategy will work on application layer and provide highly availability for Platform as a Service (PaaS) feature of cloud computing.