Enabling Stateful Functions for Stream Processing in the Programmable Data Plane

Abstract

Sensor-rich environments are crucial components of the Internet of Things ecosystem and benefit from real-time applications. Many applications perform real-time analytics on these IoT workloads by performing continuous stream processing for a window of sequence data elements. However, executing light-weight stateful functions on server CPUs adds to the communication latency of each small message in a high data rate environment, primarily due to messages traveling through a complex network stack to reach the CPU. Thus, we present an in-network function deployment architecture with low latency and low resource footprint by introducing a new compute layer. We propose an FPGA-based Switch/NIC prototype with a compute layer utilizing RISC-V soft cores and High-Level Synthesis modules. We evaluate the design for two microbenchmarks on a Zynq 7000 FPGA each, achieving less than 10 μs in latency and consuming less than 6 % of resources.