Intelligent Packet Processing for Performant Containers in IoT

Wonmi Choi, Yeonho Yoo, Kyungwoon Lee, Zhixiong Niu, Peng Cheng, Yongqiang Xiong, Gyeongsik Yang, Chuck Yoo

Abstract: This article explores the computing and communication overhead of network processing in Internet of Things (IoT) devices, focusing on containers, a major building block for the edge computing. Our experiments reveal that containers on IoT devices suffer $\sim 2.6\times $ higher CPU usage for SoftIRQ processing, ~59% less network throughput, and $2\times $ higher per-packet latency on average than native processes. While several existing studies enhance networking performance, they often sacrifice interoperability by requiring special hardware or modifying networking semantics or APIs. Thus, we design and implement a kernel networking accelerator, called SCON, that maintains interoperability, crucial for IoT devices. SCON addresses major bottlenecks in container networking through system-level profiling. We evaluate SCON with three types of IoT devices. On the Raspberry Pi 4, SCON reduces the latencies of major IoT application protocols (e.g., HTTP and MQTT) by $\sim 10\times $ , achieving a similar level of latency to the native process. Further analysis shows that SCON reduces CPU usage for SoftIRQ processing by ~26%. We also report similar improvements on the other two IoT devices. Our conclusion is that SCON is unique in significantly reducing the computing and communication overhead of container networking in IoT devices while maintaining interoperability. Furthermore, it works consistently across different types of devices, whether wired or wireless, and regardless of heavy or sporadic traffic.