In-network processing for edge computing with InLocus

As sensors and smart device infrastructure grows, networks are increasingly heterogeneous and diverse. We propose an efficient and low-latency architecture called InLocus, which facilitates stream processing at the network's edge. InLocus balances hardware-accelerated performance with the flexibility of asynchronous software control. In this paper, we extend InLocus architecture by implementing compute nodes in a more traditional cloud-based solution in the form of Apache Kafka and Twitter Heron framework, as well as by introducing a new runtime approach for the previously handwritten C Server. We utilise a flexible platform (Xilinx Zynq SoC) to compare microbenchmarks between the latter and high-level synthesis (HLS) version in programmable hardware.