Towards higher disk head utilization: extracting free bandwidth from busy disk drives
OSDI'00 Proceedings of the 4th conference on Symposium on Operating System Design & Implementation - Volume 4
Lottery scheduling: flexible proportional-share resource management
OSDI '94 Proceedings of the 1st USENIX conference on Operating Systems Design and Implementation
Argon: performance insulation for shared storage servers
FAST '07 Proceedings of the 5th USENIX conference on File and Storage Technologies
Efficient guaranteed disk request scheduling with fahrrad
Proceedings of the 3rd ACM SIGOPS/EuroSys European Conference on Computer Systems 2008
Constant Bandwidth vs Proportional Share Resource Allocation
ICMCS '99 Proceedings of the 1999 IEEE International Conference on Multimedia Computing and Systems - Volume 02
PARDA: proportional allocation of resources for distributed storage access
FAST '09 Proccedings of the 7th conference on File and storage technologies
mClock: handling throughput variability for hypervisor IO scheduling
OSDI'10 Proceedings of the 9th USENIX conference on Operating systems design and implementation
Efficient QoS for multi-tiered storage systems
HotStorage'12 Proceedings of the 4th USENIX conference on Hot Topics in Storage and File Systems
Efficient QoS for multi-tiered storage systems
HotStorage'12 Proceedings of the 4th USENIX conference on Hot Topics in Storage and File Systems
Balancing fairness and efficiency in tiered storage systems with bottleneck-aware allocation
FAST'14 Proceedings of the 12th USENIX conference on File and Storage Technologies
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The growing popularity of multi-tenant, cloud-based computing platforms is driving research into new QoS models that permit flexible sharing of the underlying infrastructure. In this paper, we re-examine the use of the commonly-used proportional-share model for resource allocation, in the context of modern heterogeneous, multi-tiered storage systems. We highlight the limitations of a conventional proportional sharing approach to resource allocation, and describe a new allocation model that provides strong isolation between clients. This improves the performance characteristics from the viewpoints of both the clients and the service provider.