Energy Modeling of Neighbor Discovery in Bluetooth Low Energy Networks
Given that current Internet of Things (IoT) applications employ many different sensors to provide information, a large number of the Bluetooth low energy (BLE) devices will be developed for IoT systems. Developing low-power and low-cost BLE advertisers is one of most challenging tasks for supporting...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2019-11-01
|
| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/19/22/4997 |
| _version_ | 1817991497674391552 |
|---|---|
| author | Bingqing Luo Jincheng Gao Zhixin Sun |
| author_facet | Bingqing Luo Jincheng Gao Zhixin Sun |
| author_sort | Bingqing Luo |
| collection | DOAJ |
| description | Given that current Internet of Things (IoT) applications employ many different sensors to provide information, a large number of the Bluetooth low energy (BLE) devices will be developed for IoT systems. Developing low-power and low-cost BLE advertisers is one of most challenging tasks for supporting the neighbor discovery process (NDP) of such a large number of BLE devices. Since the parameter setting is essential to achieve the required performance for the NDP, an energy model of neighbor discovery in BLE networks can provide beneficial guidance when determining some significant parameter metrics, such as the advertising interval, scan interval, and scan window. In this paper, we propose a new analytical model to characterize the energy consumption using all possible parameter settings during the NDP in BLE networks. In this model, the energy consumption is derived based on the Chinese remainder theorem (CRT) for an advertising event and a scanning event during the BLE NDP. In addition, a real testbed is set up to measure the energy consumption. The measurement and experimental results reveal the relationship between the average energy consumption and the key parameters. On the basis of this model, beneficial guidelines for BLE network configuration are presented to help choose the proper parameters to optimize the power consumption for a given IoT application. |
| first_indexed | 2024-04-14T01:14:07Z |
| format | Article |
| id | doaj.art-51ef499ee5564de8a5198f1763f8597c |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-14T01:14:07Z |
| publishDate | 2019-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-51ef499ee5564de8a5198f1763f8597c2022-12-22T02:20:56ZengMDPI AGSensors1424-82202019-11-011922499710.3390/s19224997s19224997Energy Modeling of Neighbor Discovery in Bluetooth Low Energy NetworksBingqing Luo0Jincheng Gao1Zhixin Sun2Jiangsu Key Laboratory of Big Data Security & Intelligent Processing, Nanjing University of Posts and Telecommunications, Nanjing 210023, ChinaJiangsu Key Laboratory of Big Data Security & Intelligent Processing, Nanjing University of Posts and Telecommunications, Nanjing 210023, ChinaLaboratory of Broadband Wireless Communication and Sensor Network Technology, Nanjing University of Posts and Telecommunications, Nanjing 210003, ChinaGiven that current Internet of Things (IoT) applications employ many different sensors to provide information, a large number of the Bluetooth low energy (BLE) devices will be developed for IoT systems. Developing low-power and low-cost BLE advertisers is one of most challenging tasks for supporting the neighbor discovery process (NDP) of such a large number of BLE devices. Since the parameter setting is essential to achieve the required performance for the NDP, an energy model of neighbor discovery in BLE networks can provide beneficial guidance when determining some significant parameter metrics, such as the advertising interval, scan interval, and scan window. In this paper, we propose a new analytical model to characterize the energy consumption using all possible parameter settings during the NDP in BLE networks. In this model, the energy consumption is derived based on the Chinese remainder theorem (CRT) for an advertising event and a scanning event during the BLE NDP. In addition, a real testbed is set up to measure the energy consumption. The measurement and experimental results reveal the relationship between the average energy consumption and the key parameters. On the basis of this model, beneficial guidelines for BLE network configuration are presented to help choose the proper parameters to optimize the power consumption for a given IoT application.https://www.mdpi.com/1424-8220/19/22/4997bluetooth low energyneighbor discoveryenergy consumption analysisinternet of things |
| spellingShingle | Bingqing Luo Jincheng Gao Zhixin Sun Energy Modeling of Neighbor Discovery in Bluetooth Low Energy Networks Sensors bluetooth low energy neighbor discovery energy consumption analysis internet of things |
| title | Energy Modeling of Neighbor Discovery in Bluetooth Low Energy Networks |
| title_full | Energy Modeling of Neighbor Discovery in Bluetooth Low Energy Networks |
| title_fullStr | Energy Modeling of Neighbor Discovery in Bluetooth Low Energy Networks |
| title_full_unstemmed | Energy Modeling of Neighbor Discovery in Bluetooth Low Energy Networks |
| title_short | Energy Modeling of Neighbor Discovery in Bluetooth Low Energy Networks |
| title_sort | energy modeling of neighbor discovery in bluetooth low energy networks |
| topic | bluetooth low energy neighbor discovery energy consumption analysis internet of things |
| url | https://www.mdpi.com/1424-8220/19/22/4997 |
| work_keys_str_mv | AT bingqingluo energymodelingofneighbordiscoveryinbluetoothlowenergynetworks AT jinchenggao energymodelingofneighbordiscoveryinbluetoothlowenergynetworks AT zhixinsun energymodelingofneighbordiscoveryinbluetoothlowenergynetworks |