Gayana Chandrasekara


Adaptive Quorums for Cloud Storage Systems


Tese submetida para provas de mestrado em Engenharia Informática e de Computadores Instituto Superior Técnico, Universidade de Lisboa.

Abstract

Cloud storage systems rely on replication for reliability. Typically, each data object is stored in multiple nodes to ensure that data remains available in face of node or network faults. Quorum systems are a practical way to ensure that clients observe consistent data even if some of the replicas are slower or unavailable. Previous work has shown that the performance of a quorum based storage system can vary greatly depending on the workload characterisation and that significant gains can be achieved by carefully selecting the size of write and read quorums. In this work we are interested in multi-tenant storage systems, that are faced to heterogeneous works. In these systems, for optimal performance, different quorums may need to be applied to different data. Unfortunately, keeping different quorum systems for different objects significantly increases the amount of metadata that the storage system needs to manage. The challenge is to find suitable tradeoffs among the size of the metadata and the performance of the resulting system. The thesis explores a strategy that consists in identifying which tenants and/or objects are the major sources of bottlenecks in the storage system and then performing fine-grain optimization for just those objects, while treating the rest in bulk. We have implemented a prototype of our system and assessed the merits of the approach experimentally.

Publicações

Adaptive Quorums for Cloud Storage Systems
Gayana Chandrasekara
MSc Thesis. Instituto Superior Técnico, Universidade de Lisboa.
July, 2015.
Available BibTeX, MSC Thesis, and extended abstract.
Q-OPT: Self-tuning Quorum System for Strongly Consistent Software Defined Storage
M. Couceiro, G. Chandrasekara, M. Bravo, M. Hiltunen, P. Romano, L. Rodrigues.
In Proceedings of the 16th ACM/IFIP/USENIX Middleware conference, Vancouver, Canada, December 2015.

Luís Rodrigues