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ISTC-CC Abstract
Fairness and Isolation in Multi-Tenant Storage as
Optimization Decomposition
ACM SIGOPS Operating System Review (OSR), 2013.
David Shue, Michael J. Freedman, Anees Shaikh*
Princeton University
*IBM Research
Shared storage services enjoy wide adoption in commercial clouds. But most systems today provide weak performance isolation and fairness between tenants, if at all. Most approaches to multi-tenant resource allocation are based either on per-VM allocations or hard rate limits that assume uniform workloads to achieve high utilization. Instead, Pisces, our system for shared key-value storage, achieves datacenter-wide per-tenant performance isolation and fairness.
Pisces achieves per-tenant weighted fair sharing of system resources across the entire shared service, even when partitions belonging to different tenants are co-located and when demand for different partitions is skewed or time-varying. The focus of this paper is to highlight the optimization model that motivates the decomposition of Pisces's fair sharing problem into four complementary mechanisms -- partition placement, weight allocation, replica selection, and weighted fair queuing -- that operate on different time-scales to provide system-wide max-min fairness. An evaluation of our Pisces storage prototype achieves nearly ideal (0:98 Min-Max Ratio) fair sharing, strong performance isolation, and robustness to skew and shifts in tenant demand.
FULL PAPER: pdf
