Empirical Analysis of LoRaWAN Adaptive Data Rate for Mobile Internet of Things Applications-Reference-Cited by-同舟云学术

Empirical Analysis of LoRaWAN Adaptive Data Rate for Mobile Internet of Things Applications

Published:2019 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2019 on Wireless of the Students, by the Students, and for the Students Workshop - S3'19
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Author:

Kousias Konstantinos¹,Caso Giuseppe²,Alay Özgü²,Lemic Filip³

Affiliation:

1. Simula Research Laboratory, Oslo, Norway

2. Simula Metropolitan Center for Digital Engineering, Oslo, Norway

3. Internet and Data Lab, University of Antwerp - imec, Antwerp, Belgium

Publisher

ACM Press

Reference10 articles.

1. Khaled Q Abdelfadeel, Victor Cionca, and Dirk Pesch. 2018. A fair adaptive data rate algorithm for LoRaWAN. arXiv preprint arXiv:1801.00522 (2018).

2. Michiel Aernouts, Rafael Berkvens, Koen Van Vlaenderen, and Maarten Weyn. 2018. Sigfox and LoRaWAN datasets for fingerprint localization in large urban and rural areas. Data 3, 2 (2018), 13.

3. Sara Amendola, Rossella Lodato, Sabina Manzari, Cecilia Occhiuzzi, and Gaetano Marrocco. 2014. RFID technology for IoT-based personal healthcare in smart spaces. IEEE Internet of Things Journal 1, 2 (2014), 144--152.

4. Martin C Bor, John Vidler, and Utz Roedig. 2016. LoRa for the Internet of Things. In International Conference on Embedded Wireless Systems and Networks (EWSN), Vol. 16. 361--366.

5. Bin Guo, ZhuWang, Zhiwen Yu, YuWang, Neil Y Yen, Runhe Huang, and Xingshe Zhou. 2015. Mobile crowd sensing and computing: The review of an emerging human-powered sensing paradigm. ACM Computing Surveys (CSUR) 48, 1 (2015), 7.

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