TY - JOUR
T1 - Performance Analysis Models of BLE Neighbor Discovery
T2 - A Survey
AU - Luo, Bingqing
AU - Yao, Yudong
AU - Sun, Zhixin
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2021/6/1
Y1 - 2021/6/1
N2 - As Internet-of-Things (IoT) applications today utilize many diverse devices to collect information, Bluetooth low energy (BLE), featuring low power and low cost, is one of the most promising wireless solutions. To meet the requirements of diverse IoT applications, the neighbor discovery process (NDP) in BLE networks requires low cost and low latency, which is one of the most challenging tasks in supporting such a large number of BLE devices. Since the choice of BLE parameters is essential for achieving the required performance of BLE NDP, many performance analysis models have been proposed, aiming to provide guidance for the parameter configuration in IoT applications. This article reviews and studies the BLE NDP models and BLE performance analysis models proposed over the period 2012-2020, considering the advantages and constraints in utilizing these models in IoT. The performance analysis models are divided into two categories: 1) probabilistic models and 2) Chinese reminder theory-based models. The model design, performance metrics, deployment constraints, analysis results, and use cases are discussed for research, development, and applications.
AB - As Internet-of-Things (IoT) applications today utilize many diverse devices to collect information, Bluetooth low energy (BLE), featuring low power and low cost, is one of the most promising wireless solutions. To meet the requirements of diverse IoT applications, the neighbor discovery process (NDP) in BLE networks requires low cost and low latency, which is one of the most challenging tasks in supporting such a large number of BLE devices. Since the choice of BLE parameters is essential for achieving the required performance of BLE NDP, many performance analysis models have been proposed, aiming to provide guidance for the parameter configuration in IoT applications. This article reviews and studies the BLE NDP models and BLE performance analysis models proposed over the period 2012-2020, considering the advantages and constraints in utilizing these models in IoT. The performance analysis models are divided into two categories: 1) probabilistic models and 2) Chinese reminder theory-based models. The model design, performance metrics, deployment constraints, analysis results, and use cases are discussed for research, development, and applications.
KW - Bluetooth low energy (BLE)
KW - neighbor discovery
KW - parameter optimizing
KW - performance analysis
UR - http://www.scopus.com/inward/record.url?scp=85098781873&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85098781873&partnerID=8YFLogxK
U2 - 10.1109/JIOT.2020.3046263
DO - 10.1109/JIOT.2020.3046263
M3 - Review article
AN - SCOPUS:85098781873
VL - 8
SP - 8734
EP - 8746
JO - IEEE Internet of Things Journal
JF - IEEE Internet of Things Journal
IS - 11
M1 - 9302738
ER -