21st International Conference on Data Engineering (ICDE'05) (2005)
Apr. 5, 2005 to Apr. 8, 2005
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICDE.2005.116
Koustuv Dasgupta , IBM India Research Lab
Sugata Ghosal , IBM India Research Lab
Rohit Jain , IBM India Research Lab
Upendra Sharma , IBM India Research Lab
Akshat Verma , IBM India Research Lab
Logical reorganization of data and requirements of differentiated QoS in information systems necessitate bulk data migration by the underlying storage layer. Such data migration needs to ensure that regular client I/Os are not impacted significantly while migration is in progress. We formalize the data migration problem in a unified admission control framework that captures both the performance requirements of client I/Os and the constraints associated with migration. We propose an adaptive rate-control based data migration methodology, QoSMig, that achieves the optimal client performance in a differentiated QoS setting, while ensuring that the specified migration constraints are met. QoSMig uses both long term averages and short term forecasts of client traffic to compute a migration schedule. We present an architecture based on Service Level Enforcement Discipline for Storage (SLEDS) that supports QoSMig. Our trace-driven experimental study demonstrates that QoSMig provides significantly better I/O performance as compared to existing migration methodologies.
S. Ghosal, U. Sharma, K. Dasgupta, A. Verma and R. Jain, "QoSMig: Adaptive Rate-Controlled Migration of Bulk Data in Storage Systems," 21st International Conference on Data Engineering (ICDE'05)(ICDE), Tokyo, Japan, 2005, pp. 816-827.