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Adaptive Device Discovery in Bluetooth Low Energy Networks

Bluetooth Low Energy (BLE) is a newly emerged technology targeting at low-power, low-cost wireless communications within medium or short range. Since BLE is well designed in favor of Wireless Body Area Networks (WBANs) or Wireless Personal Area Networks (WPANs), fast network access has been considered an important issue for users. This paper studies the performance about BLE device discovery particularly with multiple devices. An analytical model is developed, based on classical ALOHA analysis, in consideration of three advertising channels of BLE. In addition, an enhanced mechanism is proposed enabling BLE scanner/initiator to learn the network contention and adjust parameters accordingly, so as to achieve lower latency. Through extensive simulations, the model has been validated highly accurate, and the proposed mechanism has shown its effectiveness in reducing unexpected long latency in crowd BLE networks.