The efficiency of storage systems is a key factor to ensure sustainability in data centers devoted to provide cloud services. A proper management of storage infrastructures can ensure the best trade off between costs, reliability and quality of service, enabling the provider to be competitive in the market. Heterogeneity of nodes, and the need for frequent expansion and reconfiguration of the subsystems fostered the development of efficient approaches that replace traditional data replication, by exploiting more advanced techniques, such the ones that leverage erasure codes. In this paper we use an ad-hoc discrete event simulation approach to study the performances of replication and erasure coding with different parametric configurations, aiming at the minimization of overheads while obtaining the desired reliability. The approach is demonstrated with a practical application to the erasure coding plugins of the increasingly popular CEPH distributed file system.

Modeling replication and erasure coding in large scale distributed storage systems based on CEPH

GRIBAUDO, MARCO;
2016-01-01

Abstract

The efficiency of storage systems is a key factor to ensure sustainability in data centers devoted to provide cloud services. A proper management of storage infrastructures can ensure the best trade off between costs, reliability and quality of service, enabling the provider to be competitive in the market. Heterogeneity of nodes, and the need for frequent expansion and reconfiguration of the subsystems fostered the development of efficient approaches that replace traditional data replication, by exploiting more advanced techniques, such the ones that leverage erasure codes. In this paper we use an ad-hoc discrete event simulation approach to study the performances of replication and erasure coding with different parametric configurations, aiming at the minimization of overheads while obtaining the desired reliability. The approach is demonstrated with a practical application to the erasure coding plugins of the increasingly popular CEPH distributed file system.
2016
Digitally Supported Innovation: A Multi-Disciplinary View on Enterprise, Public Sector and User Innovation
978-3-319-40264-2
978-3-319-40265-9
978-3-319-40264-2
978-3-319-40265-9
CEPH; Cloud computing and big data infrastructures; Erasure codes; Performance modeling; Storage systems; Management Information Systems; Management of Technology and Innovation; Information Systems and Management; Information Systems; Computer Science Applications1707 Computer Vision and Pattern Recognition
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1004573
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