An Analysis on the Number of Advertisements for Device Discovery in the Bluetooth Low Energy Network

저전력 블루투스 네트워크에서 장치 탐색을 위한 Advertising 횟수에 관한 분석

  • Kim, Myoung Jin (Dept. of Information and Communications Eng., Hankuk University of Foreign Studies)
  • 김명진 (한국외국어대학교 정보통신공학과)
  • Received : 2016.04.14
  • Accepted : 2016.07.25
  • Published : 2016.08.25


Bluetooth Low Energy (BLE) protocol has attracted attention as a promising technology for low data throughput and low energy wireless sensor networks. Fast device discovery is very important in a BLE based wireless network. It is necessary to configure the network to work with minimized energy consumption because the BLE network nodes are expected to operate a long time typically on a coin cell battery. However, since it is difficult to obtain low energy and low latency at the same time, the BLE standard introduces wide range setting of parameters related to device discovery process and let the network operators to set up parameter values for the application. Therefore, it is necessary to analyze the performance of device discovery according to the related parameter values prior to BLE network operation. In this paper we analyze the expected value and the cumulative distribution function of the number of advertisements for device discovery in the BLE network. In addition, we propose a scheme for controlling the interval between advertising events that can improve the performance of device discovery without increasing energy consumption.


Supported by : 한국외국어대학교


  1. Bluetooth SIG, "Bluetooth Core Specification Version 4.0," Jul. 2010.
  2. ZigBee Alliance, "ZigBee specification," Dec. 2004.
  3. T. Zhang, J. Lu, and F. Hu, "Bluetooth Low Energy for Wearable Sensor-based Healthcare Systems," Proc. 2014 Health Innovations and Point-of-Care Technologies Conf., Oct., 2014.
  4. B. Zhou, et. al., "A Bluetooth Low Energy Approach for Monitoring Electrocardiography and Respiration," Proc. 2013 IEEE 15th International Conf. on e-Health Networking, Applications and Services (Healthcom), 2013.
  5. R. Fazel-Rezai, M. Pauls, and D. Slawinski, "A Low-Cost Biomedical Signal Transceiver based on a Bluetooth Wireless System," Proc. 29th Annual International Conf. of the IEEE EMBS, Aug., 2007.
  6. W. Bronzi, R. Frank, G. Castignani, and T. Engel, "Bluetooth Low Energy for Inter-Vehicular Communications," Proc. 2014 IEEE Vehicular Networking Conf. (VNC), 2014.
  7. J.-R. Lin, T. Talty, and O. K. Tonguz, "On the Potential of Bluetooth Low Energy Technology for Vehicular Applications," IEEE Commun. Mag., pp. 267-275, Jan. 2015,
  8. C. Drula, C. Amza, F. Rousssseau, and A. Duda, "Adaptive energy conserving algorithms for neighbor discovery in opportunistic Bluetooth networks," IEEE Journal on Selected Areas in Communications, Vol.25(1), pp. 96-107, Jan. 2007.
  9. S. Basagni, R. Bruno, and C. Petrioli, "Device Discovery in Bluetooth Networks: A Scatternet Perspective," Lecture Notes in Computer Science, 2006, Vol. 2345/2006.
  10. M. Duflot, M. Kwiatkowska, G. Norman, and D. Parker, "A formal analysis of bluetooth device discovery," International Journal on Software Tools for Technology Transfer, Vol.8(6), pp. 621-632, 2006.
  11. J. Liu, C. Chen, and Y. Ma, "Modeling Neighbor Discovery in Bluetooth Low Energy Networks," IEEE Communications Letters, Vol. 16, No. 9, pp. 1439-1441, Sep. 2012.
  12. C. Gomez, I. Demirkol, and J. Paradells, "Modeling the Maximum Throughput of Bluetooth Low Energy in an Error-Prone Link," IEEE Communications Letters, Vol. 15, No. 11, pp. 1187-1189, Nov. 2011.