Evaluation Through Realistic Simulations of File Replication Strategies for Large Heterogeneous Distributed Systems

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.

[1]  Kavitha Ranganathan,et al.  Simulation Studies of Computation and Data Scheduling Algorithms for Data Grids , 2003, Journal of Grid Computing.

[2]  Isabel Campos Plasencia,et al.  Validation of Grid Middleware for the European Grid Infrastructure , 2014, Journal of Grid Computing.

[3]  Johan Montagnat,et al.  A Virtual Imaging Platform for Multi-Modality Medical Image Simulation , 2013, IEEE Transactions on Medical Imaging.

[4]  Rajkumar Buyya,et al.  iFogSim: A toolkit for modeling and simulation of resource management techniques in the Internet of Things, Edge and Fog computing environments , 2016, Softw. Pract. Exp..

[5]  Henri Casanova,et al.  Versatile, scalable, and accurate simulation of distributed applications and platforms , 2014, J. Parallel Distributed Comput..

[6]  Hugues Benoit-Cattin,et al.  Simulating Application Workflows and Services Deployed on the European Grid Infrastructure , 2013, 2013 13th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing.

[7]  E. Deelman,et al.  Data replication strategies in grid environments , 2002, Fifth International Conference on Algorithms and Architectures for Parallel Processing, 2002. Proceedings..

[8]  Ming Lei,et al.  Data Replication and Power Consumption in Data Grids , 2010, 2010 IEEE Second International Conference on Cloud Computing Technology and Science.

[9]  Albert Y. Zomaya,et al.  A Proactive Non-Cooperative Game-Theoretic Framework for Data Replication in Data Grids , 2008, 2008 Eighth IEEE International Symposium on Cluster Computing and the Grid (CCGRID).

[10]  Xiaoyan Hong,et al.  An on-line replication strategy to increase availability in Data Grids , 2008, Future Gener. Comput. Syst..

[11]  E. Lanciotti,et al.  DIRAC3 – the new generation of the LHCb grid software , 2009 .

[12]  Satoshi Matsuoka,et al.  Access-pattern and bandwidth aware file replication algorithm in a grid environment , 2008, 2008 9th IEEE/ACM International Conference on Grid Computing.

[13]  Mohammad Bsoul,et al.  A Round-based Data Replication Strategy , 2016, IEEE Transactions on Parallel and Distributed Systems.

[14]  Miron Livny,et al.  Data placement for scientific applications in distributed environments , 2007, 2007 8th IEEE/ACM International Conference on Grid Computing.

[15]  Hugues Benoit-Cattin,et al.  Modeling Distributed Platforms from Application Traces for Realistic File Transfer Simulation , 2017, 2017 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID).

[16]  Peter C. J. Graham,et al.  Adaptive popularity-driven replica placement in hierarchical data grids , 2010, The Journal of Supercomputing.

[17]  Tristan Glatard,et al.  Optimizing jobs timeouts on clusters and production grids , 2007, Seventh IEEE International Symposium on Cluster Computing and the Grid (CCGrid '07).

[18]  Ching-Hsien Hsu,et al.  File replication, maintenance, and consistency management services in data grids , 2010, The Journal of Supercomputing.