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Efficient scheduling in distributed computing on grid

Kaya, Özgür
Today many computing resources distributed geographically are idle much of time. The aim of the grid computing is collecting these resources into a single system. It helps to solve problems that are too complex for a single PC. Scheduling plays a critical role in the efficient and effective management of resources to achieve high performance on grid computing environment. Due to the heterogeneity and highly dynamic nature of grid, developing scheduling algorithms for grid computing involves some challenges. In this work, we concentrate on efficient scheduling of distributed tasks on grid. We propose a novel scheduling heuristic for bag-of-tasks applications. The proposed algorithm primarily makes use of history based runtime estimation. The history stores information about the applications whose runtimes and other specific properties are recorded during the previous executions. Scheduling decisions are made according to similarity between the applications. Definition of similarity is an important aspect of this approach, apart from the best resource allocation. The aim of this scheduling algorithm (HISA-History Injected Scheduling Algorithm) is to define and find the similarity, and assign the job to the most suitable resource, making use of the similarity. In our evaluation, we use Grid simulation tool called GridSim. A number of intensive experiments with various simulation settings have been conducted. Based on the experimental results, the effectiveness of HISA scheduling heuristic is studied and compared to the other scheduling algorithms embedded in GridSim. The results show that history injection improves the performance of future job submissions on a grid.