research-article

SoNIC: classifying interference in 802.15.4 sensor networks

Authors:

Frederik Hermans,

Lars-Åke Norden,

Per GunningbergAuthors Info & Claims

IPSN '13: Proceedings of the 12th international conference on Information processing in sensor networks

Pages 55 - 66

https://doi.org/10.1145/2461381.2461392

Published: 08 April 2013 Publication History

Abstract

Sensor networks that operate in the unlicensed 2.4~GHz frequency band suffer cross-technology radio interference from a variety of devices, e.g., Bluetooth headsets, laptops using WiFi, or microwave ovens. Such interference has been shown to significantly degrade network performance. We present SoNIC, a system that enables resource-limited sensor nodes to detect the type of interference they are exposed to and select an appropriate mitigation strategy. The key insight underlying SoNIC is that different interferers disrupt individual 802.15.4 packets in characteristic ways that can be detected by sensor nodes. In contrast to existing approaches to interference detection, SoNIC does not rely on active spectrum sampling or additional hardware, making it lightweight and energy-efficient.

In an office environment with multiple interferers, a sensor node running SoNIC correctly detects the predominant interferer 87% of the time. To show how sensor networks can benefit from SoNIC, we add it to a mobile sink application to improve the application's packet reception ratio under interference.

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Cited By

Yao JHuang HSu JXie RZheng XWu K(2024)Enabling Cross-Technology Coexistence for ZigBee Devices Through Payload EncodingIEEE Transactions on Mobile Computing10.1109/TMC.2023.334583023:8(8289-8306)Online publication date: Aug-2024
https://doi.org/10.1109/TMC.2023.3345830
Xu WWan HWang HCheng NChen QZhou HGuo S(2024)Fast Packet Loss Inferring via Personalized Simulation-Reality DistillationIEEE Transactions on Mobile Computing10.1109/TMC.2023.3281725(1-10)Online publication date: 2024
https://doi.org/10.1109/TMC.2023.3281725
Dargie WKidane Z(2024)Mitigating Cross-Technology Interference in Low-Power Wireless Networks2024 33rd International Conference on Computer Communications and Networks (ICCCN)10.1109/ICCCN61486.2024.10637646(1-8)Online publication date: 29-Jul-2024
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Index Terms

SoNIC: classifying interference in 802.15.4 sensor networks
1. Hardware
  1. Hardware test
  2. Robustness

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Published In

cover image ACM Conferences

IPSN '13: Proceedings of the 12th international conference on Information processing in sensor networks

April 2013

372 pages

ISBN:9781450319591

DOI:10.1145/2461381

General Chair:
Tarek Abdelzaher
University of Illinois, Urbana-Champaign
,
Program Chairs:
Kay Römer
University of Lübeck & ETH Zurich
,
Raj Rajkumar
Carnegie Mellon University

Copyright © 2013 ACM.

Permission to make digital or hard copies of all or part 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 components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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IEEE Signal Processing Society
SIGBED: ACM Special Interest Group on Embedded Systems

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 08 April 2013

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IPSN 2013

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SIGBED

IPSN 2013: The 12th International Conference on Information Processing in Sensor Networks

April 8 - 11, 2013

Pennsylvania, Philadelphia, USA

Acceptance Rates

IPSN '13 Paper Acceptance Rate 24 of 115 submissions, 21%;

Overall Acceptance Rate 143 of 593 submissions, 24%

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Cited By

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https://doi.org/10.1109/TMC.2023.3345830
Xu WWan HWang HCheng NChen QZhou HGuo S(2024)Fast Packet Loss Inferring via Personalized Simulation-Reality DistillationIEEE Transactions on Mobile Computing10.1109/TMC.2023.3281725(1-10)Online publication date: 2024
https://doi.org/10.1109/TMC.2023.3281725
Dargie WKidane Z(2024)Mitigating Cross-Technology Interference in Low-Power Wireless Networks2024 33rd International Conference on Computer Communications and Networks (ICCCN)10.1109/ICCCN61486.2024.10637646(1-8)Online publication date: 29-Jul-2024
https://doi.org/10.1109/ICCCN61486.2024.10637646
Yao JLou WXie RJiao XWu K(2023)Mitigating Cross-Technology Interference Through Fast Signal IdentificationIEEE Transactions on Vehicular Technology10.1109/TVT.2022.321366372:2(2521-2534)Online publication date: Feb-2023
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Su JYao JXie RWu K(2023)DeepSpectrum: A Deep-Learning-based Spectrum Identification for Wireless Signals2023 19th International Conference on Mobility, Sensing and Networking (MSN)10.1109/MSN60784.2023.00094(636-643)Online publication date: 14-Dec-2023
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Cao CDong WZhang WGao Y(2023)WiEdge: Edge Computing for Audio Sensing Applications With Accurate Wireless Link PredictionIEEE Internet of Things Journal10.1109/JIOT.2022.317366810:5(3982-3994)Online publication date: 1-Mar-2023
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Hasan AKhan B(2023)Deep learning aided wireless interference identification for coexistence management in the ISM bandsWireless Networks10.1007/s11276-023-03389-329:7(3311-3331)Online publication date: 3-Jun-2023
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Yao JWu KYao JWu K(2023)Cross-Technology Interference Management Through Frequency-Domain DesignCross-Technology Coexistence Design for Wireless Networks10.1007/978-981-99-1670-2_4(33-50)Online publication date: 20-Mar-2023
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Yao JWu KYao JWu K(2023)Cross-Technology Interference Management Through Time-Domain DesignCross-Technology Coexistence Design for Wireless Networks10.1007/978-981-99-1670-2_3(23-31)Online publication date: 20-Mar-2023
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