Performance evaluation of device discovery in bluetooth le with probabilistic model checking

Yusuke Matsuo; Daisuke Umehara; Hidekazu Murata; Satoshi Denno

doi:10.1109/APSITT.2015.7217125

Performance evaluation of device discovery in bluetooth le with probabilistic model checking

Yusuke Matsuo, Daisuke Umehara, Hidekazu Murata, Satoshi Denno

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Citations (Scopus)

Abstract

The device discovery in Bluetooth is needed before establishing data communications. Almost all Bluetooth slaves are battery-powered so that they should connect with a master through the device discovery for a short time. To prevent the worst case scenario with long device discovery in Bluetooth, the events with long device discovery should be estimated in advance. However, it is intractable to estimate the exact longest device discovery time with Monte Carlo simulations or mathematical analysis because of the probabilistic behavior. In this paper, we reveal the longest device discovery time and the maximum energy consumption in Bluetooth Low Energy (LE) with a probabilistic model checking tool, PRISM. The results show that some parameters in Bluetooth LE will largely affect the energy consumption so that their design criteria will be desired to reduce the energy consumption.

Original language	English
Title of host publication	2015 10th Asia-Pacific Symposium on Information and Telecommunication Technologies, APSITT 2015
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	58-60
Number of pages	3
ISBN (Print)	9784885522987
DOIs	https://doi.org/10.1109/APSITT.2015.7217125
Publication status	Published - Aug 20 2015
Event	10th Asia-Pacific Symposium on Information and Telecommunication Technologies, APSITT 2015 - Colombo, Sri Lanka Duration: Aug 4 2015 → Aug 7 2015

Other

Other	10th Asia-Pacific Symposium on Information and Telecommunication Technologies, APSITT 2015
Country/Territory	Sri Lanka
City	Colombo
Period	8/4/15 → 8/7/15

Keywords

Advertising
Bluetooth
Clocks
Energy consumption
Performance evaluation
Probabilistic logic
Timing

ASJC Scopus subject areas

Computer Networks and Communications
Information Systems

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/APSITT.2015.7217125

Cite this

Matsuo, Y., Umehara, D., Murata, H., & Denno, S. (2015). Performance evaluation of device discovery in bluetooth le with probabilistic model checking. In 2015 10th Asia-Pacific Symposium on Information and Telecommunication Technologies, APSITT 2015 (pp. 58-60). [7217125] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/APSITT.2015.7217125

Performance evaluation of device discovery in bluetooth le with probabilistic model checking. / Matsuo, Yusuke; Umehara, Daisuke; Murata, Hidekazu; Denno, Satoshi.

2015 10th Asia-Pacific Symposium on Information and Telecommunication Technologies, APSITT 2015. Institute of Electrical and Electronics Engineers Inc., 2015. p. 58-60 7217125.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Matsuo, Y, Umehara, D, Murata, H & Denno, S 2015, Performance evaluation of device discovery in bluetooth le with probabilistic model checking. in 2015 10th Asia-Pacific Symposium on Information and Telecommunication Technologies, APSITT 2015., 7217125, Institute of Electrical and Electronics Engineers Inc., pp. 58-60, 10th Asia-Pacific Symposium on Information and Telecommunication Technologies, APSITT 2015, Colombo, Sri Lanka, 8/4/15. https://doi.org/10.1109/APSITT.2015.7217125

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abstract = "The device discovery in Bluetooth is needed before establishing data communications. Almost all Bluetooth slaves are battery-powered so that they should connect with a master through the device discovery for a short time. To prevent the worst case scenario with long device discovery in Bluetooth, the events with long device discovery should be estimated in advance. However, it is intractable to estimate the exact longest device discovery time with Monte Carlo simulations or mathematical analysis because of the probabilistic behavior. In this paper, we reveal the longest device discovery time and the maximum energy consumption in Bluetooth Low Energy (LE) with a probabilistic model checking tool, PRISM. The results show that some parameters in Bluetooth LE will largely affect the energy consumption so that their design criteria will be desired to reduce the energy consumption.",

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N2 - The device discovery in Bluetooth is needed before establishing data communications. Almost all Bluetooth slaves are battery-powered so that they should connect with a master through the device discovery for a short time. To prevent the worst case scenario with long device discovery in Bluetooth, the events with long device discovery should be estimated in advance. However, it is intractable to estimate the exact longest device discovery time with Monte Carlo simulations or mathematical analysis because of the probabilistic behavior. In this paper, we reveal the longest device discovery time and the maximum energy consumption in Bluetooth Low Energy (LE) with a probabilistic model checking tool, PRISM. The results show that some parameters in Bluetooth LE will largely affect the energy consumption so that their design criteria will be desired to reduce the energy consumption.

AB - The device discovery in Bluetooth is needed before establishing data communications. Almost all Bluetooth slaves are battery-powered so that they should connect with a master through the device discovery for a short time. To prevent the worst case scenario with long device discovery in Bluetooth, the events with long device discovery should be estimated in advance. However, it is intractable to estimate the exact longest device discovery time with Monte Carlo simulations or mathematical analysis because of the probabilistic behavior. In this paper, we reveal the longest device discovery time and the maximum energy consumption in Bluetooth Low Energy (LE) with a probabilistic model checking tool, PRISM. The results show that some parameters in Bluetooth LE will largely affect the energy consumption so that their design criteria will be desired to reduce the energy consumption.

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Performance evaluation of device discovery in bluetooth le with probabilistic model checking

Abstract

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Keywords

ASJC Scopus subject areas

UN SDGs

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