On the Benefits of Transparent Compression for Cost-Effective Cloud Data StorageReport as inadecuate

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* Corresponding author 1 GRAND-LARGE - Global parallel and distributed computing LRI - Laboratoire de Recherche en Informatique, LIFL - Laboratoire d-Informatique Fondamentale de Lille, UP11 - Université Paris-Sud - Paris 11, Inria Saclay - Ile de France, CNRS - Centre National de la Recherche Scientifique : UMR8623

Abstract : Infrastructure-as-a-Service IaaS cloud computing has revolutionized the way we think of acquiring computational resources: it allows users to deploy virtual machines VMs at large scale and pay only for the resources that were actually used throughout the runtime of the VMs. This new model raises new challenges in the design and development of IaaS middleware: excessive storage costs associated with both user data and VM images might make the cloud less attractive, especially for users that need to manipulate huge data sets and a large number of VM images. Storage costs result not only from storage space utilization, but also from bandwidth consumption: in typical deployments, a large number of data transfers between the VMs and the persistent storage are performed, all under high performance requirements. This paper evaluates the trade-off resulting from transparently applying data compression to conserve storage space and bandwidth at the cost of slight computational overhead. We aim at reducing the storage space and bandwidth needs with minimal impact on data access performance. Our solution builds on BlobSeer, a distributed data management service specifically designed to sustain a high throughput for concurrent accesses to huge data sequences that are distributed at large scale. Extensive experiments demonstrate that our approach achieves large reductions at least 40% of bandwidth and storage space utilization, while still attaining high performance levels that even surpass the original no compression performance levels in several data-intensive scenarios.

keyword : high performance cloud storage virtual machine image storage data intensive applications transparent compression

Author: Bogdan Nicolae -

Source: https://hal.archives-ouvertes.fr/


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