Discovery Latency Analysis of Ultra-Dense Internet-of-Things Networks

This paper presents a comprehensive performance analysis and optimization of ultra-dense Internet-of-Things (IoT) networks. While the high density of Bluetooth Low Energy (BLE) devices in IoT networks improves wireless coverage and enhances connectivity, these coexisting devices can also lead to increased interference and collisions, degrading device discovery performance and increasing the network's overall latency. In this work, we provide a mathematical analysis of the discovery latency in densely deployed BLE networks. Our mathematical model constructs a Markov chain model that implements the impacts of packet collisions and duplication on discovery latency. Based on a thorough performance analysis, we propose a novel duplication-avoidance protocol in which BLE devices cooperatively adjust advertising and minimize the network's overall discovery latency. Our simulation results shows that the proposed novel duplication-avoidance protocol consistently reduces latency compared to the standard discovery protocol in densely deployed BLE networks, with relative improvements ranging from 7.63% to 8.16%.