Anti-Collision Broadcasting Scheme Based on iBeacon in Internet of Things

被引：0
|
作者：
Xü L.-Y. [1 ]
Han D.-Q. [2 ]
Liu W. [1 ]
机构：
[1] School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing
[2] School of Information and Communications Engineering, Beijing University of Posts and Telecommunications, Beijing
来源：
Beijing Youdian Daxue Xuebao/Journal of Beijing University of Posts and Telecommunications | 2020年 / 43卷 / 02期
关键词：
Bluetooth low energy; Broadcast collision; Internet of things; Latency analysis;
D O I：
10.13190/j.jbupt.2019-096
中图分类号：
学科分类号：
摘要：
Aiming at the problem of signal collision in the dense Internet of Things environment, an anti-collision broadcasting scheme was proposed which can group respond to multiple nodes in time and reduce the collision rate. The collision probability was analyzed by multi-period iteration, and a theoretical model was established which effectively solves the serious channel collision in concurrent broadcasting of large-scale sensor nodes. Monte Carlo simulation was created to evaluate indicators such as latency, capacity, and power consumption. The key parameters affecting the performance were analyzed. The model calculation results are consistent with the simulation results. Compared with the unresponsive broadcasting protocol, the broadcast response mechanism can effectively confirm, reduce 23% network delay and 90% broadcast collision, and increase the system capacity by 100%. © 2020, Editorial Department of Journal of Beijing University of Posts and Telecommunications. All right reserved.
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页码：66 / 73
页数：7
相关论文
共 17 条
  • [1] He Zhiqiang, Cui Binyue, Zhou Wei, Et al., A proposal of interaction system between visitor and collection in museum hall by iBeacon, 2015 10th International Conference on Computer Science & Education (ICCSE), pp. 427-430, (2015)
  • [2] Vochin M, Vulpe A, Boicescu L, Et al., An intelligent low-power displaying system withr integrated emergency alerting capability, Sensors, 19, 3, (2019)
  • [3] Chen Zhenghua, Zhu Qingchang, Soh Y C., Smartphone inertial sensor-based indoor localization and tracking with iBeacon corrections, IEEE Transactions on Industrial Informatics, 12, 4, pp. 1540-1549, (2016)
  • [4] Wu Xudong, Shen Ruofei, Fu Luoyi, Et al., iBILL: using iBeacon and inertial sensors for accurate indoor localization in large open areas, IEEE Access, 5, pp. 14589-14599, (2017)
  • [5] Vy T D, Shin Y., iBeacon indoor localization using trusted-Ranges model, International Journal of Distributed Sensor Networks, 15, 1, (2019)
  • [6] Varela P M, Otsuki Ohtsuki T., Discovering Co-located walking groups of people using iBeacon technology, IEEE Access, 4, pp. 6591-6601, (2016)
  • [7] Bak S, Suh Y J., Designing and implementing an enhanced bluetooth low energy scanner with user-level channel awareness and simultaneous channel scanning, IEICE Transactions on Information and Systems, E102, 3, pp. 640-644, (2019)
  • [8] Shan Gaoyang, Im S Y, Roh B H., Optimal AdvInterval for BLE scanning in different number of BLE devices environment, 2016 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), pp. 1031-1032, (2016)
  • [9] Shan Gaoyang, Lee B U, Shin S H, Et al., Design and implementation of simulator for analysis of BLE broadcast signal collision, 2017 International Conference on Information Networking (ICOIN), pp. 448-452, (2017)
  • [10] Cho K, Park W, Hong M, Et al., Analysis of latency performance of bluetooth low energy (BLE) networks, Sensors, 15, 1, pp. 59-78, (2014)
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