Dynamic Adaptation of Checkpoints and Rescheduling in Grid Computing

Abstract

Grid is a form distributed computing mainly to virtualilze and utilize geographically distributed idle resources. A grid is a distributed computational and storage environment often composed of heterogeneous autonomously managed subsystems. As a result varying resource availability becomes common place, often resulting in loss and delay of executing jobs. To ensure good performance fault tolerance should be taken into account. Here we address the fault tolerance in terms of resource failure. Commonly utilized techniques to achieve fault tolerance is periodic checkpointing, which periodically saves the jobs state. But an inappropriate checkpointing interval leads to delay in the job execution, and reduces the throughput. Hence in the proposed work, the strategy used to achieve fault tolerance is by dynamically adapting the checkpoints based on current status and history of failure information of the resource, which is maintained in the Information server. The Last failure time and Mean failure time based algorithm dynamically modifies the frequency of checkpoint interval, hence increases the throughput by reducing the unnecessary checkpoint overhead. In case of resource failure, the proposed Fault Index Based Rescheduling (FIBR) algorithm reschedules the job from the failed resource to some other available resource with the least Fault-index value and executes the job from the last saved checkpoint. This ensures the job to be executed within the deadline with increased throughput and helps in making the grid environment trust worthy.

A novel adaptive checkpointing method based on information obtained from workflow structure

“…In their work [10], Theresa et al propose two dynamic checkpoint strategies: Last Failure time-based Checkpoint Adaptation (LFCA) and Mean Failure time-based Checkpoint Adaptation (MFCA), which takes into account the stability of the system and the probability of failure concerning individual resources.…”

From volunteer to trustable computing: Providing QoS-aware scheduling mechanisms for multi-grid computing environments

“…In that work, by means of simulation, they propose a similar approach to ours, trying to both increase the utilization and meet job deadlines, but without providing any differentiation of QoS levels. These rescheduling techniques can also be used to try to provide fault tolerance performance, such as the work presented in [52], where this is provided by changing the frequency of the checkpointing process based on current status and history of failure information of the resource and by rescheduling the jobs when those failures happen. However, they do not migrate jobs to increase utilization or QoS differentiation amongst users.…”

New aspect of investigating fault sensitivity of scientific workflows

“…The authors of [5,6,7,8] make some assumptions or gather statistics about failure distribution of individual resources or resource systems and based on these values and calculations adjust fault tolerant mechanisms. For example Theresa et al propose in their work [8] two dynamic checkpoint strategies: Last Failure time based Checkpoint Adaptation (LFCA) and Mean Failure time based Checkpoint Adaptation (MFCA) which takes into account the stability of the system and the probability of failure concerning the individual resources. Young in [5] has already in 1974 defined his formula for the optimum periodic checkpoint interval which is based on the checkpointing cost and the mean time between failures (MTBF) with the assumption that failure intervals follow an exponential distribution.…”