Self-Optimizing Bluetooth Low Energy Networks for Industrial IoT Applications

Abstract

This letter develops an efficient self-optimizing algorithm for Bluetooth Low Energy (BLE) networks in industrial IoT (IIoT) applications. The ultra-dense nature of IIoT applications implies that BLE networks are associated with a high probability of packet collisions, increasing the data collection latency. Determining the optimal packet transmission interval that minimizes the data collection latency is very challenging due to the non-linearity of this problem. We derive an analytic solution by which to realize an optimal advertising interval in a closed-form expression and prove its optimality and uniqueness. Based on a simple closed-form solution, we develop a low-complexity self-optimizing algorithm that minimizes the data collection latency. Simulation results confirm that the analytic results are accurate and that the proposed algorithm autonomously optimizes BLE networks.