Autonomic ElasticWorkflow Advanced Reservation Planning Algorithm for Grids and Clouds – EWARP

Advanced Reservation (AR) is used to guarantee resource provisioning for many different types of applications including workflows. This technique is still under a huge controversy in both Business and Research communities because of its potentiality of reducing resource utilization. Most of the works proposed in this domain suggest reservation for the whole workflow schedule, and on all available resources at the same time, which worsen the problem of resource utilization. Many solutions are introduced to improve resource utilization under advanced reservation through generating relaxed and elastic reservation plans that local scheduling systems could modify to improve utilization and decrease internal fragmentation. These solutions depend mainly on changing rigid AR, which considered to be the most difficult kind of reservation, into relaxed and elastic ones through adding extra time on the resulted schedule and then distributing it on all tasks of the workflow. This paper presents a new autonomic algorithm (EWARP) for producing elastic reservation plans for workflow applications which doesn’t add extra times. Instead, it depends on exploiting the timing gaps produced by the different scheduling algorithms. The new algorithm use the technique of discovering timing gaps, but modifies it, and adds to it to be used for producing an elastic reservation plan for workflows. The results presented in this paper demonstrate how the proposed algorithm outperforms existing works in the fields by a lower bound approximating 25%.This shows that (EWARP) algorithm offer efficient and practical solutions for the problem of scheduling workflow applications under QoS constrains.

A checkpoint/recovery Model based on work stealing for grid applications

The study is researching the fault tolerance in the large distributed environments such as grid computing and clusters of computers in order to find the most effective ways to deal with the errors associated with the crash one of the devices in the environment or network disconnection to ensure the continuity of the application in the presence of the faults.In this paper we study a model of the distributed environment and the parallel applications within it. Then we provide a checkpoint mechanism that will enable us to ensure continuity of the work used by a virtual representation of the application (macro dataflow) and suitable for the applications which uses work stealing algorithm to distribute the tasks which are implemented in heterogeneous and dynamic environment. This mechanism will add a simple cost to the cost of parallel execution as a result of keeping part of the work during fault-free execution. The study also provides a mathematical model to calculate the time complexity i.e. the cost of this proposed mechanism.