Fair Allocation of Asymmetric Operations in Storage Systems

Abstract

Managing the trade-off between efficiency and fairness in a storage system is challenging due to high variability in workload behavior. Most workloads are made up of a mix of asymmetric operations (e.g. read/write, sequential/random, or striped/isolated I/Os) in different proportions, which places different resource demands on the storage device. The problem is to allocate device resources to the heterogeneous workloads fairly while maintaining high device throughput. In this paper, we present a new model for fair allocation of heterogeneous workloads with different ratios of asymmetric operations. We propose an adaptive scheme that chooses between two policies-the traditional Time-Balanced Allocation (TBA) and our proposed Bottleneck-Balanced Allocation (BBA)-based on workload characteristics. The fairness and throughput of these allocation policies are established through formal analysis. Our algorithms are tested with an adaptive, dynamic scheduler implemented in a simulation testbed, and the results validate the performance benefits of our approach.