Scalable QoS for Distributed Storage Clusters using Dynamic Token Allocation

The paper addresses the problem of providing performance QoS guarantees in a clustered storage system. Multiple related storage objects are grouped into logical containers called buckets, which are distributed over the servers based on the placement policies of the storage system. QoS is provided at the level of buckets. The service credited to a bucket is the aggregate of the IOs received by its objects at all the servers. The service depends on individual time-varying demands and congestion at the servers. We present a token-based, coarse-grained approach to providing IO reservations and limits to buckets. We propose pShift, a novel token allocation algorithm that works in conjunction with token-sensitive scheduling at each server to control the aggregate IOs received by each bucket on multiple servers. pShift determines the optimal token distribution based on the estimated bucket demands and server IOPS capacities. Compared to existing approaches, pShift has far smaller overhead, and can be accelerated using parallelization and approximation. Our experimental results show that pShift provides accurate QoS among the buckets with different access patterns, and handles runtime demand changes well.