%0 Conference Paper %1 Hermans:2013:SCI:2461381.2461392 %A Hermans, Frederik %A Rensfelt, Olof %A Voigt, Thiemo %A Ngai, Edith %A Norden, Lars-\AAke %A Gunningberg, Per %B Proceedings of the 12th international conference on Information processing in sensor networks %C New York, NY, USA %D 2013 %I ACM %K classification detection experimental interference jamming toread wireless %P 55--66 %R 10.1145/2461381.2461392 %T SoNIC: classifying interference in 802.15.4 sensor networks %U http://doi.acm.org/10.1145/2461381.2461392 %X 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. %@ 978-1-4503-1959-1

@inproceedings{Hermans:2013:SCI:2461381.2461392, 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.}, acmid = {2461392}, added-at = {2013-10-21T10:38:41.000+0200}, address = {New York, NY, USA}, author = {Hermans, Frederik and Rensfelt, Olof and Voigt, Thiemo and Ngai, Edith and Norden, Lars-\AAke and Gunningberg, Per}, biburl = {https://www.bibsonomy.org/bibtex/2a408aa51db313a56de88402c4a12dfee/affitz}, booktitle = {Proceedings of the 12th international conference on Information processing in sensor networks}, description = {SoNIC}, doi = {10.1145/2461381.2461392}, interhash = {4983e061eb1ae4654ce9b5acb9350aae}, intrahash = {a408aa51db313a56de88402c4a12dfee}, isbn = {978-1-4503-1959-1}, keywords = {classification detection experimental interference jamming toread wireless}, location = {Philadelphia, Pennsylvania, USA}, numpages = {12}, pages = {55--66}, publisher = {ACM}, series = {IPSN '13}, timestamp = {2013-10-22T10:32:39.000+0200}, title = {SoNIC: classifying interference in 802.15.4 sensor networks}, url = {http://doi.acm.org/10.1145/2461381.2461392}, year = 2013 }