An Adaptive Parameter Setting Algorithm to Enhance Performance in Self-Organizing Bluetooth Low Energy Networks

Abstract

Bluetooth Low Energy (BLE) evolved from classical Bluetooth technologies for enabling short-range communication in different services and systems. BLE has many advantages over classical Bluetooth technologies, including low-cost deployment and low-power consumption. Recently, a very few number of research studies have been conducted to improve device discovery process of BLE. But, these studies have still some limitations. Prior studies have assumed that advertising PDUs are immediately processed as long as they are received successfully by a scanner. Practically, however, BLE devices may experience lots of collisions due to contention among neighbors, particularly in a crowded environment. With increasing number of BLE devices, delays of both device discovery and connection setup keep exponential growth, which could influence user experience in terms of either time or energy consumption. In this paper, an enhanced mechanism is proposed to enable BLE advertisers and scanners to learn the network contention and adjust their parameters accordingly, so as to achieve fast discovery latency. Through extensive simulations, the proposed mechanism has shown its effectiveness to reduce unexpected long latency in crowded BLE networks.