Minerva: An automated resource provisioning tool for large-scale storage systems
ACM Transactions on Computer Systems (TOCS)
Data migration to minimize the average completion time
SODA '03 Proceedings of the fourteenth annual ACM-SIAM symposium on Discrete algorithms
Hippodrome: Running Circles Around Storage Administration
FAST '02 Proceedings of the Conference on File and Storage Technologies
Autonomic storage system based on automatic learning
HiPC'04 Proceedings of the 11th international conference on High Performance Computing
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This paper addresses the types of QoS dissatisfaction caused by imbalance of the initial I/O workload pattern and storage performance across multiple storage servers in a storage cluster. It next proposes a systematic scheme to resolve the QoS problem that periodically monitors the QoS satisfaction level, analyzes the causes of the QoS problem, and performs data migration based on the analysis result. Finally, it verifies the effectiveness of the proposed scheme under a simulation environment under the different types of QoS dissatisfaction.