Evaluation through realistic simulations of file replication strategies for large heterogeneous distributed systems

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Abstract

File replication is widely used to reduce file transfer times and improve data availability in large distributed systems. Replication techniques are often evaluated through simulations, however, most simulation platform models are oversimplified, which questions the applicability of the findings to real systems. In this paper, we investigate how platform models influence the performance of file replication strategies on large heterogeneous distributed systems, based on common existing techniques such as prestaging and dynamic replication. The novelty of our study resides in our evaluation using a realistic simulator. We consider two platform models: a simple hierarchical model and a detailed model built from execution traces. Our results show that conclusions depend on the modeling of the platform and its capacity to capture the characteristics of the targeted production infrastructure. We also derive recommendations for the implementation of an optimized data management strategy in a scientific gateway for medical image analysis.

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APA

Chai, A., Camarasu-Pop, S., Glatard, T., Benoit-Cattin, H., & Suter, F. (2019). Evaluation through realistic simulations of file replication strategies for large heterogeneous distributed systems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11339 LNCS, pp. 409–420). Springer Verlag. https://doi.org/10.1007/978-3-030-10549-5_32

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