存储系统的智能后台管理
A Smart Background Scheduler for Storage Systems
摘要：
在当今的企业存储系统中，支持的数据服务（如快照删除或驱动器重建）如果与大量前台IO一起内联执行，可能会造成巨大的性能干扰，通常会导致SLO（服务级别目标）缺失。典型的存储系统应用程序（如Web或虚拟桌面基础架构）遵循可了解和预测的重复性高/低工作负载模式。我们提出了一个基于优先级的后台调度程序，学习这种重复模式，并允许存储系统保持峰值性能，进而满足服务水平目标（SLO），同时支持一些数据服务。当前台IO需求加剧时，系统资源专用于服务前台IO请求，并且只要预测显示存储池具有剩余容量，则可以延迟的任何后台处理都被记录为在未来的空闲周期中处理。智能后台调度器采用资源分区模型，只要前台IO不受影响，就允许前台和后台IO一起执行，其中调度器利用任何空闲周期来清除后台债务。使用跟踪从EQUIPMENT应用程序，我们展示了我们的技术如何超越静态限制递延的背景债务和提高SLO违规的方法，从54.6%，当使用一个固定的背景债务水印只有6.2%，如果动态设置我们的智能后台调度。
英文摘要：
In today's enterprise storage systems, supported data services such as snapshot delete or drive rebuild can cause tremendous performance interference if executed inline along with heavy foreground IO, often leading to missing SLOs (Service Level Objectives). Typical storage system applications such as web or VDI (Virtual Desktop Infrastructure) follow a repetitive high/low workload pattern that can be learned and forecasted. We propose a priority-based background scheduler that learns this repetitive pattern and allows storage systems to maintain peak performance and in turn meet service level objectives (SLOs) while supporting a number of data services. When foreground IO demand intensifies, system resources are dedicated to service foreground IO requests and any background processing that can be deferred are recorded to be processed in future idle cycles as long as forecast shows that storage pool has remaining capacity. The smart background scheduler adopts a resource partitioning model that allows both foreground and background IO to execute together as long as foreground IOs are not impacted where the scheduler harness any free cycle to clear background debt. Using traces from VDI application, we show how our technique surpasses a method that statically limit the deferred background debt and improve SLO violations from 54.6% when using a fixed background debt watermark to merely a 6.2% if dynamically set by our smart background scheduler.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
