demonstration

Demo: A Cell-level Traffic Generator for LoRa Networks

Authors:

Michele Gucciardo,

Ilenia Tinnirello,

Domenico GarlisiAuthors Info & Claims

MobiCom '17: Proceedings of the 23rd Annual International Conference on Mobile Computing and Networking

Pages 474 - 476

https://doi.org/10.1145/3117811.3119862

Published: 04 October 2017 Publication History

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Abstract

In this demo we present and validate a LoRa cell traffic generator, able to emulate the behavior of thousands of low-rate sensor nodes deployed in the same cell, by using a single Software Defined Radio (SDR) platform. Differently from traditional generators, whose goal is creating packet flows which emulate specific applications and protocols, our focus is generating a combined radio signal, as seen by a gateway, given by the super-position of the signals transmitted by multiple sensors simultaneously active on the same channel. We argue that such a generator can be of interest for testing different network planning solutions for LoRa networks.

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Cited By

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De Keersmaeker FCao YNdonda GSadre R(2023)A Survey of Public IoT Datasets for Network Security ResearchIEEE Communications Surveys & Tutorials10.1109/COMST.2023.328894225:3(1808-1840)Online publication date: Nov-2024
https://doi.org/10.1109/COMST.2023.3288942
Almuhaya MJabbar WSulaiman NSulaiman A(2022)An Overview on LoRaWAN Technology Simulation ToolsAdvances on Intelligent Informatics and Computing10.1007/978-3-030-98741-1_29(345-358)Online publication date: 30-Mar-2022
https://doi.org/10.1007/978-3-030-98741-1_29
Garlisi DTinnirello IBianchi GCuomo F(2021)Capture Aware Sequential Waterfilling for LoRaWAN Adaptive Data RateIEEE Transactions on Wireless Communications10.1109/TWC.2020.303863820:3(2019-2033)Online publication date: Mar-2021
https://doi.org/10.1109/TWC.2020.3038638
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Index Terms

Demo: A Cell-level Traffic Generator for LoRa Networks
1. Networks
  1. Network properties
    1. Network range
      1. Very long-range networks
      2. Wide area networks
  2. Network types
    1. Wireless access networks
      1. Wireless local area networks

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Information & Contributors

Information

Published In

MobiCom '17: Proceedings of the 23rd Annual International Conference on Mobile Computing and Networking

October 2017

628 pages

ISBN:9781450349161

DOI:10.1145/3117811

General Chair:
Kobus Van der Merwe
University of Utah
,
Program Chairs:
Ben Greenstein
Google, USA
,
Kannan Srinivasan
Ohio State University, USA

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 04 October 2017

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Author Tags

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Demonstration

Funding Sources

project SymbIoTe H2020-ICT-2015

Conference

MobiCom '17

Sponsor:

SIGMOBILE

MobiCom '17: The 23rd Annual International Conference on Mobile Computing and Networking

October 16 - 20, 2017

Utah, Snowbird, USA

Acceptance Rates

MobiCom '17 Paper Acceptance Rate 35 of 186 submissions, 19%;

Overall Acceptance Rate 440 of 2,972 submissions, 15%

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De Keersmaeker FCao YNdonda GSadre R(2023)A Survey of Public IoT Datasets for Network Security ResearchIEEE Communications Surveys & Tutorials10.1109/COMST.2023.328894225:3(1808-1840)Online publication date: Nov-2024
https://doi.org/10.1109/COMST.2023.3288942
Almuhaya MJabbar WSulaiman NSulaiman A(2022)An Overview on LoRaWAN Technology Simulation ToolsAdvances on Intelligent Informatics and Computing10.1007/978-3-030-98741-1_29(345-358)Online publication date: 30-Mar-2022
https://doi.org/10.1007/978-3-030-98741-1_29
Garlisi DTinnirello IBianchi GCuomo F(2021)Capture Aware Sequential Waterfilling for LoRaWAN Adaptive Data RateIEEE Transactions on Wireless Communications10.1109/TWC.2020.303863820:3(2019-2033)Online publication date: Mar-2021
https://doi.org/10.1109/TWC.2020.3038638
Garlisi DMangione SGiuliano FCroce DGarbo GTinnirello I(2021)Interference Cancellation for LoRa Gateways and Impact on Network CapacityIEEE Access10.1109/ACCESS.2021.31080219(128133-128146)Online publication date: 2021
https://doi.org/10.1109/ACCESS.2021.3108021
Croce DGucciardo MMangione SSantaromita GTinnirello I(2020)LoRa Technology Demystified: From Link Behavior to Cell-Level PerformanceIEEE Transactions on Wireless Communications10.1109/TWC.2019.294887219:2(822-834)Online publication date: Feb-2020
https://doi.org/10.1109/TWC.2019.2948872
Croce DGucciardo MSantaromita GMangione STinnirello I(2020)Performance of LoRa technology: link-level and cell-level performanceLPWAN Technologies for IoT and M2M Applications10.1016/B978-0-12-818880-4.00010-7(181-197)Online publication date: 2020
https://doi.org/10.1016/B978-0-12-818880-4.00010-7
Croce DGarlisi DGiuliano FValvo AMangione STinnirello I(2019)Performance of LoRa for Bike-Sharing Systems2019 AEIT International Conference of Electrical and Electronic Technologies for Automotive (AEIT AUTOMOTIVE)10.23919/EETA.2019.8804519(1-6)Online publication date: Jul-2019
https://doi.org/10.23919/EETA.2019.8804519

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Demo: Achieving robust sensor networks through close coordination between narrow-band power line and low-power wireless communications

AndroGenerator: An automated and configurable android app network traffic generation system

Coverage and Lifetime Optimization of Wireless Sensor Networks with Gaussian Distribution

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