| Abstract |
To enable the Internet of Things (IoT) to scale at the level of next-generation smart cities and grids, there is a need for a cost-effective infrastructure for hosting IoT analytics applications. Offload and acceleration via smartNICs have been shown to provide benefits to these workloads. However, even with offload, long-term analysis on IoT data still needs to operate on a massive number of device updates, often in the form of small messages. Despite offloading, the ingestion of these updates continues to present server bottlenecks. In this article, we present domain-specific compression and batching engines that leverage the unique properties of IoT messages to reduce the load on analytics servers and improve their scalability. Using a prototype system based on InnovaFlex programmable smartNICs and several representative IoT benchmarks, we demonstrate that these techniques achieve up to 73 improvement over existing offload approaches. © 2023 IEEE. |
