Economical Task Scheduling Algorithm for Grid Computing Systems

Task duplication is an effective scheduling technique for reducing the response time of workflow applications in dynamic grid computing systems. Task duplication based scheduling algorithms generate shorter schedules without sacrificing efficiency but leave the computing resources over consumed due to the heavily duplications. In this paper, we try to minimize the duplications of tasks from the schedule obtained using an effective duplication based scheduling heuristic without affecting the overall schedule length (makespan) of grid application. Here, we suggested an economical duplication based intelligent scheduling heuristic called economical duplication scheduling in grid (EDS-G). The simulation results show that EDS-G algorithm generates better schedule with lesser number of duplications and remarkably less resource consumption as compared with HLD, LDBS in the simulated heterogeneous grid computing environments

A Survey of Pipelined Workflow Scheduling: Models and Algorithms

International audienceA large class of applications need to execute the same workflow on different data sets of identical size. Efficient execution of such applications necessitates intelligent distribution of the application components and tasks on a parallel machine, and the execution can be orchestrated by utilizing task-, data-, pipelined-, and/or replicated-parallelism. The scheduling problem that encompasses all of these techniques is called pipelined workflow scheduling, and it has been widely studied in the last decade. Multiple models and algorithms have flourished to tackle various programming paradigms, constraints, machine behaviors or optimization goals. This paper surveys the field by summing up and structuring known results and approaches

QoS-aware predictive workflow scheduling

This research places the basis of QoS-aware predictive workflow scheduling. This research novel contributions will open up prospects for future research in handling complex big workflow applications with high uncertainty and dynamism. The results from the proposed workflow scheduling algorithm shows significant improvement in terms of the performance and reliability of the workflow applications

Flexible Rollback Recovery in Dynamic Heterogeneous Grid Computing

Abstract—Large applications executing on Grid or cluster architectures consisting of hundreds or thousands of computational nodes create problems with respect to reliability. The source of the problems are node failures and the need for dynamic configuration over extensive runtime. This paper presents two fault-tolerance mechanisms called Theft-Induced Checkpointing and Systematic Event Logging. These are transparent protocols capable of overcoming problems associated with both benign faults, i.e., crash faults, and node or subnet volatility. Specifically, the protocols base the state of the execution on a dataflow graph, allowing for efficient recovery in dynamic heterogeneous systems as well as multithreaded applications. By allowing recovery even under different numbers of processors, the approaches are especially suitable for applications with a need for adaptive or reactionary configuration control. The low-cost protocols offer the capability of controlling or bounding the overhead. A formal cost model is presented, followed by an experimental evaluation. It is shown that the overhead of the protocol is very small, and the maximum work lost by a crashed process is small and bounded. Index Terms—Grid computing, rollback recovery, checkpointing, event logging. Ç