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Short tail:taming tail latency for erasure-code-based in-memory systems

Frontiers of Information Technology & Electronic Engineering 2022年第11期23卷 1646-1657页

作者： Yun TENG Zhiyue LI Jing HUANG Guangyan ZHANG College of Computer Science and Technology Jilin UniversityChangchun 130012China Department of Computer Science and Technology Tsinghua UniversityBeijing 100084China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin UniversityChangchun 130012China Beijing National Research Center for Information Science and Technology(Tsinghua University) Beijing 100084China

In-memory systems with erasure coding(EC)enabled are widely used to achieve high performance and data availability.However,as the scale of clusters grows,the server-level fail-slow problem is becoming increasingly frequent,which can create long tail latency.The influence of long tail latency is further amplified in EC-based systems due to the synchronous nature of multiple EC sub-operations.In this paper,we propose an EC-enabled in-memory storage system called Shorttail,which can achieve consistent performance and low latency for both reads and writes.First,Shorttail uses a lightweight request monitor to track the performance of each memory node and identify any fail-slow node.Second,Shorttail selectively performs degraded reads and redirected writes to avoid accessing fail-slow nodes.Finally,Shorttail posts an adaptive write strategy to reduce write amplification of small writes.We implement Shorttail on top of Memcached and compare it with two baseline systems.The experimental results show that Shorttail can reduce the P99 tail latency by up to 63.77%;it also brings significant improvements in the median latency and average latency.

关键词： Erasure code In-memory system Node fail-slow Small write tail latency

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A globally shared resource paradigm for encoded storage systems in the public cloud

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Fundamental Research 2024年第3期4卷 642-650页

作者： Zhiyue Li Guangyan Zhang Department of Computer Science and Technology Tsinghua UniversityBeijing 100084China Beijing National Research Center for Information Science and Technology Tsinghua UniversityBeijing 100084China

Public clouds favor sharing of storage resources,in which many tenants acquire bandwidth and storage capacity from a shared storage pool.To provide high availability,data are often encoded to provide fault tolerance with low storage costs.Regarding this,efficiently organizing an encoded storage system for shared I/Os is critical for application performance.This is usually hard to achieve as different applications have different stripe configurations and fault tolerance levels.In this paper,we first study the block trace from the Alibaba cloud,and find that I/O patterns of modern applications prefer the resource sharing scheme.Based on this,we propose a globally shared resource paradigm for encoded storage system in the public cloud.The globally shared resource paradigm can provide balanced load and fault tolerance for numerous disk pool sizes and arbitrary application stripe configurations.Furthermore,we demonstrate with two case studies that our theory can help address the device-specific problems of HDD and SSD RAID arrays with slight modifications:comparing the existing resource partition and resource sharing methods,our theory can promote the rebuild speed of the HDD RAID arrays by 2.5,and reduce the P99 tail latency of the SSD arrays by up to two orders of magnitude.

关键词： Public cloud Encoded storage Load balancing RAID reconstruction tail latency

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Labeled yon Neumann Architecture for Software-Defined Cloud

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Journal of Computer Science & Technology 2017年第2期32卷 219-223页

作者： Yun-Gang Bao Sa Wang, Member, CCF State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China University of Chinese Academy of Sciences Beijing 100049 China

As cloud computing is moving forward rapidly, cloud providers have been encountering great challenges： long tail latency, low utilization, and high interference. They intend to co-locate multiple workloads on a single server to improve the resource utilization. But the co-located applications suffer from severe performance interference and long tail latency, which lead to unpredictable user experience. To meet these challenges, software-defined cloud has been proposed to facilitate tighter coordination among application, operating system and hardware. Users＇ quality of service （QoS） requirements could be propagated all the way down to the hardware with differential management mechanisms. However, there is little hardware support to maintain and guarantee users＇ QoS requirements. To this end, this paper proposes Labeled von Neumann Architecture （LvNA）, which introduces a labelling mechanism to convey more software＇s semantic information such as QoS and security to the underlying hardware. LvNA is able to correlate labels with various entities, e.g., virtual machine, process and thread, and propagate labels in the whole machine and program differentiated services based on rules. We consider LvNA to be a fundamental hardware support to the software-defined cloud.

关键词： software-defined cloud von Neumann architecture tail latency performance interference

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