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蓝牙低功耗(BLE)网络的延迟性能分析。

Analysis of latency performance of bluetooth low energy (BLE) networks.

作者信息

Cho Keuchul, Park Woojin, Hong Moonki, Park Gisu, Cho Wooseong, Seo Jihoon, Han Kijun

机构信息

School of Computer Science and Engineering, Kyungpook National University, Daegu 702-701, Korea.

Software R&D Center, Samsung Electronics Co., Ltd., Suwon 443-742, Korea.

出版信息

Sensors (Basel). 2014 Dec 23;15(1):59-78. doi: 10.3390/s150100059.

Abstract

Bluetooth Low Energy (BLE) is a short-range wireless communication technology aiming at low-cost and low-power communication. The performance evaluation of classical Bluetooth device discovery have been intensively studied using analytical modeling and simulative methods, but these techniques are not applicable to BLE, since BLE has a fundamental change in the design of the discovery mechanism, including the usage of three advertising channels. Recently, there several works have analyzed the topic of BLE device discovery, but these studies are still far from thorough. It is thus necessary to develop a new, accurate model for the BLE discovery process. In particular, the wide range settings of the parameters introduce lots of potential for BLE devices to customize their discovery performance. This motivates our study of modeling the BLE discovery process and performing intensive simulation. This paper is focused on building an analytical model to investigate the discovery probability, as well as the expected discovery latency, which are then validated via extensive experiments. Our analysis considers both continuous and discontinuous scanning modes. We analyze the sensitivity of these performance metrics to parameter settings to quantitatively examine to what extent parameters influence the performance metric of the discovery processes.

摘要

低功耗蓝牙(BLE)是一种旨在实现低成本、低功耗通信的短距离无线通信技术。经典蓝牙设备发现的性能评估已通过分析建模和模拟方法进行了深入研究,但这些技术不适用于BLE,因为BLE在发现机制的设计上有根本性变化,包括使用三个广告通道。最近,有几项工作分析了BLE设备发现的主题,但这些研究仍远不够全面。因此,有必要为BLE发现过程开发一个新的、准确的模型。特别是,参数的广泛设置为BLE设备定制其发现性能带来了很大潜力。这促使我们对BLE发现过程进行建模并进行密集模拟。本文重点构建一个分析模型,以研究发现概率以及预期发现延迟,然后通过广泛实验进行验证。我们的分析考虑了连续和不连续扫描模式。我们分析这些性能指标对参数设置的敏感性,以定量研究参数在多大程度上影响发现过程的性能指标。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e29/4327007/d4d2ff444448/sensors-15-00059f1.jpg

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