English

RASC: Enhancing Observability & Programmability in Smart Spaces

Distributed, Parallel, and Cluster Computing 2026-01-21 v1

Abstract

While RPCs form the bedrock of systems stacks, we posit that IoT device collections in smart spaces like homes, warehouses, and office buildings--which are all "user-facing"--require a more expressive abstraction. Orthogonal to prior work, which improved the reliability of IoT communication, our work focuses on improving the observability and programmability of IoT actions. We present the RASC (Request-Acknowledge-Start-Complete) abstraction, which provides acknowledgments at critical points after an IoT device action is initiated. RASC is a better fit for IoT actions, which naturally vary in length spatially (across devices) and temporally (across time, for a given device). RASC also enables the design of several new features: predicting action completion times accurately, detecting failures of actions faster, allowing fine-grained dependencies in programming, and scheduling. RASC is intended to be implemented atop today's available RPC mechanisms, rather than as a replacement. We integrated RASC into a popular and open-source IoT framework called Home Assistant. Our trace-driven evaluation finds that RASC meets latency SLOs, especially for long actions that last O(mins), which are common in smart spaces. Our scheduling policies for home automations (e.g., routines) outperform state-of-the-art counterparts by 10%-55%.

Keywords

Cite

@article{arxiv.2601.13496,
  title  = {RASC: Enhancing Observability & Programmability in Smart Spaces},
  author = {Anna Karanika and Kai-Siang Wang and Han-Ting Liang and Shalni Sundram and Indranil Gupta},
  journal= {arXiv preprint arXiv:2601.13496},
  year   = {2026}
}

Comments

16 pages, 19 figures. This paper is a preprint version of our upcoming paper of the same name in the USENIX Symposium on Networked Systems Design and Implementation (NSDI), 2026

R2 v1 2026-07-01T09:11:37.430Z