Performance analysis of device discovery of Bluetooth Low Energy (BLE) networks

Cho, Keuchul; Park, Gisu; Cho, Wooseong; Seo, Ji Hun; Han, Kijun

doi:10.1016/j.comcom.2015.10.008

Cited by 56 publications

(29 citation statements)

References 3 publications

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“…For these reasons, we believe that this dataset can be used as a tool to approximate network behaviour in similar conditions. Naturally, every real life event is di erent, but this data can be used to complement and extend the conclusions of known experiments, models and new techniques [2,4,6]. Our observations show consistent pa erns when analysing the RSSI levels of the packets received by the RPIs.…”

Section: Examples Of Usagesupporting

confidence: 61%

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CWI-ADE2016 Dataset

Cabrero

Jansen

Röggla

et al. 2017

Proceedings of the 8th ACM on Multimedia Systems Conference

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ABSTRACTe CWI-ADE2016 Dataset is a collection of more than 40 million Bluetooth Low Energy (BLE) packets and of 14 million accelerometer and temperature samples generated by wristbands that people wore in a nightclub.e data was gathered during Amsterdam Dance Event 2016 in an exclusive club experience curated around human senses, which leveraged technology as a bridge between the club and the guests. Each guest was handed a custom-made wristband with a BLE-enabled device that broadcast movement, temperature and other sensor readings. A network of Raspberry Pi receivers deployed for the occasion captured broadcast packets from wristbands and any other BLE device in the environment.is data provides a full picture of the performance of the real life deployment of a sensing infrastructure and gives insights to designing sensing platforms, understanding networks and crowds behaviour or studying opportunistic sensing. is paper describes an analysis of this dataset and some examples of usage. CCS CONCEPTS•Networks →Network performance analysis; •Applied computing →Performing arts;

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Section: Examples Of Usagesupporting

confidence: 61%

“…Tracking 450 devices per night inside an improvised club space of about 500 m 2 is challenging because of the amount of devices, the expected density in areas such as the dance oors and the limitations of BLE [2,4]. e 2.4 GHz frequency band used by BLE is shared with WiFi.…”

Section: Infrastructure: Raspberry Pi Networkmentioning

confidence: 99%

CWI-ADE2016 Dataset

Cabrero

Jansen

Röggla

et al. 2017

Proceedings of the 8th ACM on Multimedia Systems Conference

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“…Besides our proposed theory, this model is the only one which predicts upper bounds (for T a < d s , only). Further, we have considered the predicted mean latencies of the model by Cho et al [27], [28] and the accelerated simulation model by Kindt et al [26], with ∆ = 93.12 s and = 0.99 into this comparison. Figure 11.…”

Section: Discussion Of the Results Thementioning

confidence: 99%

Neighbor Discovery Latency in BLE-Like Protocols

Kindt

Saur

Balszun

et al. 2018

IEEE Trans. on Mobile Comput.

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Neighbor discovery is the procedure using which two wireless devices initiate a first contact. In low power ad-hoc networks, radios are duty-cycled and the latency until a packet meets a reception phase of another device is determined by a random process. Most research considers slotted protocols, in which the points in time for reception are temporally coupled to beacon transmissions. In contrast, many recent protocols, such as ANT/ANT+ and Bluetooth Low Energy (BLE) use a slotless, periodic-interval based scheme for neighbor discovery. Here, one device periodically broadcasts packets, whereas the other device periodically listens to the channel. Both periods are independent from each other and drawn over continuous time. Such protocols provide 3 degrees of freedom (viz., the intervals for advertising and scanning and the duration of each scan phase). Though billions of existing BLE devices rely on these protocols, neither their expected latencies nor beneficial configurations with good latency-duty-cycle relations are known. Parametrizations for the participating devices are usually determined based on a "good guess". In this paper, we for the first time present a mathematical theory which can compute the neighbor discovery latencies for all possible parametrizations. Further, our theory shows that upper bounds on the latency can be guaranteed for all parametrizations, except for a finite number of singularities. Therefore, slotless, periodic interval-based protocols can be used in applications with deterministic latency demands, which have been reserved for slotted protocols until now. Our proposed theory can be used for analyzing the neighbor discovery latencies, for tweaking protocol parameters and for developing new protocols. arXiv:1509.04366v4 [cs.NI] 18 Aug 2017Maximum deviation (max(|dcomp − dsim|)) for mean/maximum latencies dcomp, dsimComputed/Simulated latency

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“…That is why Bluetooth becomes the focus fo nterconnected by CAN-Bus with an external device ou self. ons of the Bluetooth protocol [4] was designed for the d nge but at high rate, without being possible to operate th re in a low power mode until the Bluetooth Low Energ the 4.0 protocol update. This review focused on the op ery low consumption at lower rate and the possibility mission.…”

Section: Fig 2 Bosch Information Dismentioning

confidence: 99%

New Architecture for Electric Bikes Control Based on Smartphones and Wireless Sensors

Revuelta

Villarrubia

Barriuso

et al. 2016

Advances in Intelligent Systems and Computing

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During the last years, great advances has been produced in the automotive industry, a strategic sector both nationally and internationally with a high socioeconomic impact. Many efforts have focused on providing smart environments to the final user in vehicles such as cars, capable of detecting contextual vehicle's conditions and adapting automatically to the user needs. This paper proposes an innovative solution in the automotive field consisting of a new product family which allows the transformation of a traditional bicycle to an electric bicycle by an architecture that provides the user intelligent adaptive environments and significantly improve the driving experience design enabling value-added services.

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Performance analysis of device discovery of Bluetooth Low Energy (BLE) networks

Cited by 56 publications

References 3 publications

CWI-ADE2016 Dataset

CWI-ADE2016 Dataset

Neighbor Discovery Latency in BLE-Like Protocols

New Architecture for Electric Bikes Control Based on Smartphones and Wireless Sensors

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