SearcharxivSearch

arXiv subjects

Shalni Sundram

Publications and source records attributed to Shalni Sundram.

2 recordsLinked to original sources

RASC: Enhancing Observability & Programmability in Smart Spaces

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%.

cs.DC

CoMesh: Fully-Decentralized Control for Sense-Trigger-Actuate Routines in Edge Meshes

While mesh networking for edge settings (e.g., smart buildings, farms, battlefields, etc.) has received much attention, the layer of control over such meshes remains largely centralized and cloud-based. This paper focuses on applications with sense-trigger-actuate (STA) workloads -- these are similar to the abstraction of routines popular in smart homes, but applied to larger-scale edge IoT deployments. We present CoMesh, which tackles the challenge of building local, non-cloud, and decentralized solutions for control of sense-trigger-actuate applications. At its core CoMesh uses an abstraction called k-groups to spread in a fine-grained way, the load of STA actions. Coordination within the k-group uses selective fast and cheap mechanisms rather than expensive off-the-shelf solutions. k-group selection is proactively dynamic, and occurs by using a combination of zero-message-exchange mechanisms (to reduce load) and locality sensitive hashing (to be aware of physical layout of devices). We analyze and theoretically prove the safety of CoMesh's mechanisms. Our evaluations using both simulation and Raspberry Pi lab deployments show that CoMesh is load-balanced, fast, and fault-tolerant.

cs.DC