Performance Evaluation of Bluetooth Low Energy: A Systematic Review
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TL;DR: This work reviews the main methodologies adopted to investigate BLE performance, and analyzes throughput, maximum number of connectable sensors, power consumption, latency and maximum reachable range with the aim to identify what are the current limits of BLE technology.
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Abstract: Small, compact and embedded sensors are a pervasive technology in everyday life for a wide number of applications (e.g., wearable devices, domotics, e-health systems, etc.). In this context, wireless transmission plays a key role, and among available solutions, Bluetooth Low Energy (BLE) is gaining more and more popularity. BLE merges together good performance, low-energy consumption and widespread diffusion. The aim of this work is to review the main methodologies adopted to investigate BLE performance. The first part of this review is an in-depth description of the protocol, highlighting the main characteristics and implementation details. The second part reviews the state of the art on BLE characteristics and performance. In particular, we analyze throughput, maximum number of connectable sensors, power consumption, latency and maximum reachable range, with the aim to identify what are the current limits of BLE technology. The main results can be resumed as follows: throughput may theoretically reach the limit of ~230 kbps, but actual applications analyzed in this review show throughputs limited to ~100 kbps; the maximum reachable range is strictly dependent on the radio power, and it goes up to a few tens of meters; the maximum number of nodes in the network depends on connection parameters, on the network architecture and specific device characteristics, but it is usually lower than 10; power consumption and latency are largely modeled and analyzed and are strictly dependent on a huge number of parameters. Most of these characteristics are based on analytical models, but there is a need for rigorous experimental evaluations to understand the actual limits.
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References
Bluetooth low energy profile for MPU9150 IMU data transfers
J. Pedro Amaro,Sergio Patrao,Fernando Moita,Luis Roseiro +3 more
- 01 Jan 2017
TL;DR: The BLE proprietary profile that has been implemented to transfer data in wireless mode is presented and the BLE protocol basics and the relevant options are described so that implemented systems are low power and fully compatible with the protocol.
7
A paraeducator glove for counting disabled-child behaviors that incorporates a Bluetooth Low Energy wireless link to a smart phone
Shiwei Luan,Dana Gude,Punit Prakash,Steve Warren +3 more
- 01 Jan 2014
TL;DR: A para glove design that can help to track behaviors with minimal distraction by allowing a paraeducator to touch their thumb to one of their other four fingers, where each finger represents a different behavior.
6
Modeling and analysis of performance based on Bluetooth Low Energy
Keuchul Cho,Changsu Jung,Jinbae Kim,Yongtak Yoon,Kijun Han +4 more
- 01 Nov 2015
TL;DR: The intensive analytical and simulation study provide a basis for the modeling of the BLE discovery process and investigates discovery probability as well as expected discovery latency in a wireless sensor network based on BLE, which are then validated via extensive experiments.
5
Dictionary memory based software architecture for distributed Bluetooth Low Energy host controllers enabling high coverage in consumer residential healthcare environments
R. Simon Sherratt,Balazs Janko,Terence K. L. Hui,William S. Harwin,Daniel Diaz-Sanchez +4 more
- 30 Mar 2017
TL;DR: This work presents a novel gateway software architecture based on threads being managed by dictionary memory that is deployed in a distributed interconnected set of low-cost consumer grade gateway devices using Bluetooth Low Energy that are positioned around the home.
Design of automobile intelligence control platform based on Bluetooth low energy
Kun Xia,Haibo Wang,Nan Wang,Wei Yu,Tong Zhou +4 more
- 01 Nov 2016
TL;DR: The feasibility of the entire control platform and the reliability of the system design have been verified, and the intelligence control platform has the features of high safety, stable performance, easy operation and some other advantages.
5
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