Deploying an Information Centric Smart Lighting System in the Wild

TL;DR

This paper introduces a reliable NDN-based smart lighting system that automatically adjusts lights based on occupancy and daylight, evaluated against cloud solutions for latency and scalability.

Contribution

It demonstrates a practical NDN architecture for smart home lighting, including push data, multicast, and Interest filtering, with performance benchmarking and scalability analysis.

Findings

NDN-based system reduces message latency compared to cloud solutions.

The system scales effectively with Interest filtering and FIB analysis.

Recommendations for improving NDN in IoT applications.

Abstract

In this paper, we present a NDN based smart home lighting solution where lights are automatically controlled in near real time based on occupancy and daylight. We implemented a reliable solution using NDN architecture exploiting the primitive NDN features in push based data dissemination, multicast forwarding through name prefixes and Interest filtering in application layer. Performance was evaluated benchmarking with respect to a cloud based approach in terms of message delivery latency. Scalability of the solution was also analyzed presenting an analysis on FIB scalability based on Interest filtering. Finally, from this study, we recommend and highlight a few requirements that could improve NDN for sustainable IoT applications.