2021/06/17 by Liuying Ma, Zhenqing Liu, Ma, Liuying +5 · 1 citation
Computer Science · #Advanced Data Storage Technologies #Cloud Computing and Resource Management #Computer science #Database #Distributed and Parallel Computing Systems #Embedded system #FOS: Computer and information sciences #Latency (audio) #Operating system #Parallel computing #Performance (cs.PF) #Storage management #Telecommunications #cs.PF
paper · pdf · doi:10.48550/arxiv.2106.09206
published in arXiv (Cornell University) (Cornell University) · 14 pages, 11 figures
arxiv created 2021/06/17 · openalex publication_date 2021/06/17 · arxiv updated 2021/06/18 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Consolidating latency-critical (LC) and best-effort (BE) tenants at storage backend helps to increase resources utilization. Even if tenants use dedicated queues and threads to achieve performance isolation, threads are still contend for CPU cores. Therefore, we argue that it is necessary to partition cores between LC and BE tenants, and meanwhile each core is dedicated to run a thread. Expect for frequently changing bursty load, fluctuated service time at storage backend also drastically changes the need of cores. In order to guarantee tail latency service level objectives (SLOs), the abrupt changing need of cores must be satisfied immediately. Otherwise, tail latency SLO violation happens. Unfortunately, partitioning-based approaches lack the ability to react the changing need of cores, resulting in extreme spikes in latency and SLO violation happens. In this paper, we present QWin, a tail latency SLO aware core allocation to enforce tail latency SLO at shared storage backend. QWin consists of an SLO-to-core calculation model that accurately calculates the number of cores combining with definitive runtime load determined by a flexible request-based window, and an autonomous core allocation that adjusts cores at adaptive frequency by dynamically changing core policies. When consolidating multiple LC and BE tenants, QWin outperforms the-state-of-the-art approaches in guaranteeing tail latency SLO for LC tenants and meanwhile increasing bandwidth of BE tenants by up to 31x.