Abstract
Grid computing consists of geographically distributed computing and storage resources that are used in large scale scientific applications. Job scheduling and data replication are two well-known techniques to boost the performance of Data Grid. There has been extensive research on integrating both techniques to further improve performance in Data Grid. However, most of the current works are heuristic based without performance guarantees.
Our goals are: (a) Integrating data replication and job scheduling into one framework to minimize the total job execution time in the Grid, (b) Achieving good management of the replica consistency.
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Meddeber, M., Hamadouche, H. (2020). Tasks Scheduling and Consistency Management in Mono-Masters Grid Environment. In: Hatti, M. (eds) Smart Energy Empowerment in Smart and Resilient Cities. ICAIRES 2019. Lecture Notes in Networks and Systems, vol 102. Springer, Cham. https://doi.org/10.1007/978-3-030-37207-1_44
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DOI: https://doi.org/10.1007/978-3-030-37207-1_44
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