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Erschienen in:
2013 | OriginalPaper | Buchkapitel
Data Scheduling in Data Grids and Data Centers: A Short Taxonomy of Problems and Intelligent Resolution Techniques
verfasst von : Joanna Kołodziej, Samee Ullah Khan
Erschienen in: Transactions on Computational Collective Intelligence X
Verlag: Springer Berlin Heidelberg
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Data-aware scheduling in today’s large-scale heterogeneous environments has become a major research issue. Data Grids (DGs) and Data Centers arise quite naturally to support needs of scientific communities to share, access, process, and manage large data collections geographically distributed. Data scheduling, although similar in nature with grid scheduling, is given rise to the definition of a new family of optimization problems. New requirements such as data transmission, decoupling of data from processing, data replication, data access and security are to be added to the scheduling problem are the basis for the definition of a whole taxonomy of data scheduling problems. In this paper we briefly survey the state-of-the-art in the domain. We exemplify the model and methodology for the case of data-aware independent job scheduling in computational grid and present several heuristic resolution methods for the problem.