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标签化网络栈:一种用于支持大规模物联网设备的高并发低尾延迟的云服务器框架

Labeled Network Stack: A High-Concurrency and Low-Tail Latency Cloud Server Framework for Massive IoT Devices

  • 摘要: 物联网(IOT)应用程序存在海量向云服务器的客户端连接,而且联网的IOT设备数量在显著增加。物联网服务需要数据中心兼具低尾延迟和高并发性。这项研究旨在通过为未来数据中心提出一种软硬件协同设计的标签化网络栈(LNS)技术,来确定当前主流系统的尾部延迟和并发性是否可能有一个数量级的改进。关键的创新是,一种跨层次的载荷标签机制,它可以贯穿整个网络栈来区分不同的有效负载请求,包括应用层、TCP/IP层和以太网层。这种设计可以确保全数据路径上进行数据包的优先处理和转发,以至于延迟不敏感的请求不会明显受到高优先级请求的影响。我们构建了一个数据中心服务器原型系统,使用云化的物联网应用场景,对比商用X86服务器和mTCP研究来评估标签化网络栈的设计。实验结果表明,标签化网络栈的设计可以达成尾延迟和并发性的数量级提升。在以50毫秒为99分位尾延迟阈值的情况下,单台数据中心服务器节点可以支持超过200万并发的物联网设备长连接。此外,软硬件协同的设计方法显著降低了标签化和优先处理的开销,并有效控制了高优先级请求对低优先级请求的干扰。

     

    Abstract: Internet of Things (IoT) applications have massive client connections to cloud servers, and the number of networked IoT devices is remarkably increasing. IoT services require both low-tail latency and high concurrency in datacenters. This study aims to determine whether an order of magnitude improvement is possible in tail latency and concurrency in mainstream systems by proposing a hardware-software codesigned labeled network stack (LNS) for future datacenters. The key innovation is a cross-layered payload labeling mechanism that distinguishes different requests by payload across the full network stack, including application, TCP/IP, and Ethernet layers. This type of design enables prioritized data packet processing and forwarding along the full datapath, such that latency-insensitive requests cannot significantly interfere with high-priority requests. We build a prototype datacenter server to evaluate the LNS design against a commercial X86 server and the mTCP research, using a cloud-supported IoT application scenario. Experimental results show that the LNS design can provide an order of magnitude improvement in tail latency and concurrency. A single datacenter server node can support over 2 million concurrent long-living connections for IoT devices as a 99-percentile tail latency of 50 ms is maintained. In addition, the hardware-software codesign approach remarkably reduces the labeling and prioritization overhead and constrains the interference of high-priority requests to low-priority requests.

     

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