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

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.