Abstract
The co-allocation architecture was developed in order to enable parallel downloads of datasets from multiple servers. Several co-allocation strategies have been coupled and used to exploit rate differences among various client-server links and to address dynamic rate fluctuations by dividing files into multiple blocks of equal sizes. However, a major obstacle, the idle time of faster servers having to wait for the slowest server to deliver the final block, makes it important to reduce differences in finish time among replica servers. In this paper, we propose a dynamic co-allocation scheme, namely Recursive-Adjustment Co-Allocation scheme, to improve the performance of data transfer in Data Grids. Our approach reduces the idle time spent waiting for the slowest server and decreases data transfer completion time.
This paper is supported in part by National Science Council, Taiwan ROC, under grants no. NSC92-2213-E-029-025, NSC92-2119-M-002-024, NSC93-2119-M-002-004, and NSC93-2213-E-029-026.
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Yang, CT., Yang, IH., Li, KC., Hsu, CH. (2005). A Recursive-Adjustment Co-allocation Scheme in Data Grid Environments. In: Hobbs, M., Goscinski, A.M., Zhou, W. (eds) Distributed and Parallel Computing. ICA3PP 2005. Lecture Notes in Computer Science, vol 3719. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11564621_5
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DOI: https://doi.org/10.1007/11564621_5
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