Today, companies and data centers are moving towards cloud and serverless storage systems instead of traditional file systems. As a result of such a transition, allocating sufficient resources to users and parties to satisfy their service level demands has become crucial in cloud storage. In cloud storage, the schedulability of system components and requests is of great importance to achieving QoS goals. However, the bufferbloat phenomenon in storage backends impacts the schedulability of the system. In a storage server, bufferbloat happens when the server submits all requests immediately to the storage backend due to a large buffer in the backend. In recent decades, many studies have focused on the bufferbloat as a latency problem. Nevertheless, none of these works investigate the impact of bufferbloat on the schedulability of the system. In this paper, we demonstrate that the bufferbloat impacts scheduling and performance isolation and identify utilizing admission control in the storage backend as an easy-to-adopt solution to mitigate bufferbloat. Moreover, we show that traditional static admission controls are inadequate in the face of dynamic workloads in cloud environments. Finally, we propose SlowFast CoDel, an adaptive admission control, as a starting point for developing adaptive admission control mechanisms to mitigate bufferbloat in cloud storage.
翻译:如今,公司和数据中心正在转向云存储和无服务器存储系统而不是传统的文件系统。由于这种转变,为用户和各方分配足够的资源以满足其服务水平要求已成为云存储中至关重要的问题。在云存储中,系统组件和请求的可调度性对于实现QoS目标非常重要。然而,存储后端中的缓冲区充塞现象会影响系统的可调度性。在存储服务器中,缓冲区充塞是指由于后端缓冲区过大,服务器立即将所有请求提交到后端存储时发生的问题。在过去几十年中,许多研究关注缓冲区充塞作为一种延迟问题。然而,这些工作中没有任何一个研究调查了缓冲区充塞对系统可调度性的影响。在本文中,我们证明了缓冲区充塞对调度和性能隔离的影响,并确定在存储后端中采用入场控制作为缓解缓冲区充塞的易于采用的解决方案。此外,我们展示了传统的静态入场控制在面对云环境中的动态工作负载时是不足够的。最后,我们提出了SlowFast CoDel,一种自适应入场控制机制,作为开发缓解存储云系统中缓冲区充塞问题的自适应入场控制机制的起点。