Abstract
Sensor networks operating in the 2.4 GHz band often face cross-technology interference from co-located WiFi and Bluetooth devices. To enable effective interference mitigation, a sensor network needs to know the type of interference it is exposed to. However, existing approaches to interference detection are not able to handle multiple concurrent sources of interference. In this paper, we address the problem of identifying multiple channel activities impairing a sensor network’s communication, such as simultaneous WiFi traffic and Bluetooth data transfers. We present SpeckSense, an interference detector that distinguishes between different types of interference using a unsupervised learning technique. Additionally, SpeckSense features a classifier that distinguishes between moderate and heavy channel traffic, and also identifies WiFi beacons. In doing so, it facilitates interference avoidance through channel blacklisting. We evaluate SpeckSense on common mote hardware and show how it classifies concurrent interference under real-world settings. We also show how SpeckSense improves the performance of an existing multichannel data collection protocol by 30%.
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References
Liang, C.M., Priyantha, N.B., Liu, J., Terzis, A.: Surviving Wi-Fi interference in low power ZigBee networks. In: ACM SenSys (2010)
Iyer, V., Woehrle, M., Langendoen, K.: Chrysso – a multi-channel approach to mitigate external interference. In: IEEE SECON (2011)
Hauer, J., Willig, A., Wolisz, A.: Mitigating the effects of RF interference through RSSI-based error recovery. In: Silva, J.S., Krishnamachari, B., Boavida, F. (eds.) EWSN 2010. LNCS, vol. 5970, pp. 224–239. Springer, Heidelberg (2010)
Boano, C.A., Voigt, T., Tsiftes, N., Mottola, L., Römer, K., Zúñiga, M.A.: Making sensornet MAC protocols robust against interference. In: Silva, J.S., Krishnamachari, B., Boavida, F. (eds.) EWSN 2010. LNCS, vol. 5970, pp. 272–288. Springer, Heidelberg (2010)
Chowdhury, K.R., Akyildiz, I.F.: Interferer classification, channel selection and transmission adaptation for wireless sensor networks. In: ICC (2009)
Hermans, F., Rensfelt, O., Voigt, T., Ngai, E., Nordén, L.-Å., Gunningberg, P.: SoNIC: classifying interference in 802.15.4 sensor networks. In: IPSN (2013)
Zacharias, S., Newe, T., O’Keeffe, S., Lewis, E.: A lightweight classification algorithm for external sources of interference in IEEE 802.15.4-based wireless sensor networks operating at the 2.4 GHz. IJDSN (2014)
Zacharias, S., Newe, T., O’Keeffe, S., Lewis, E.: Identifying sources of interference in RSSI traces of a single IEEE 802.15. 4 channel. In: ICWMC (2012)
Zhou, R., Xiong, Y., Xing, G., Sun, L., Ma, J.: ZiFi: wireless LAN discovery via ZigBee interference signatures. In: ACM MobiCom, pp. 49–60 (2010)
Boano, C.A., Voigt, T., Noda, C., Romer, K., Zuniga, M.: JamLab: Augmenting sensornet testbeds with realistic and controlled interference generation. In: ACM IPSN (2011)
MacQueen, J., et al.: Some methods for classification and analysis of multivariate observations. In: Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability, California, USA, vol. 1(281-297), p. 14 (1967)
Iyer, V.G., Hermans, F., Voigt, T.: Detecting and avoiding multiple sources of interference in the 2.4 GHZ spectrum. Department of Information Technology, Uppsala University, Tech. Rep. 2014-023 (December 2014)
Gao, Y., Niu, J., Zhou, R., Xing, G.: Zifind: Exploiting cross-technology interference signatures for energy-efficient indoor localization. In: IEEE Infocom 2013, pp. 2940–2948 (2013)
Ferrari, F., Zimmerling, M., Thiele, L., Saukh, O.: Efficient network flooding and time synchronization with Glossy. In: IPSN, pp. 73–84 (2011)
Tang, L., Sun, Y., Gurewitz, O., Johnson, D.B.: EM-MAC: a dynamic multichannel energy-efficient MAC protocol for wireless sensor networks. In: ACM MobiHoc 2011, p. 23 (2011)
Al Nahas, B., Duquennoy, S., Iyer, V., Voigt, T.: Low-Power Listening Goes Multi-Channel. In: IEEE DCOSS, Marina Del Rey, CA, USA (2014)
Musaloiu-E, R., Terzis, A.: Minimising the effect of WiFi interference in 802.15. 4 wireless sensor networks. IJSN 3(1), 43–54 (2008)
Doddavenkatappa, M., Chan, M.C., Ananda, A.L.: Indriya: A low-cost, 3D wireless sensor network testbed. In: Korakis, T., Li, H., Tran-Gia, P., Park, H.-S. (eds.) TridentCom 2011. LNICST, vol. 90, pp. 302–316. Springer, Heidelberg (2012)
Buettner, M., Yee, G.V., Anderson, E., Han, R.: X-MAC: a short preamble MAC protocol for duty-cycled wireless sensor networks. In: ACM SenSys 2006, pp. 307–320 (2006)
Jain, R.: The art of computer systems performance analysis. John Wiley & Sons (2008)
Boers, N.M., Nikolaidis, I., Gburzynski, P.: Sampling and classifying interference patterns in a wireless sensor network. ACM TOSN 2012 9(1), 2 (2012)
Bloessl, B., Joerer, S., Mauroner, F., Dressler, F.: Low-Cost Interferer Detection and Classification using TelosB Sensor Motes. In: ACM MobiCom, pp. 403–406 (2012)
Ansari, J., Ang, T., Mähönen, P.: WiSpot: fast and reliable detection of Wi-Fi networks using IEEE 802.15.4 radios. In: ACM MobiWac 2011, pp. 35–44 (2011)
Rayanchu, S., Patro, A., Banerjee, S.: Catching whales and minnows using WiFiNet: deconstructing non-WiFi interference using WiFi hardware. In: Proc. of USENIX NSDI (2012)
Ansari, J., Mähönen, P.: Channel selection in spectrum agile and cognitive MAC protocols for wireless sensor networks. In: ACM MobiWac (2010)
Noda, C., Prabh, S., Alves, M., Boano, C., Voigt, T.: Quantifying the channel quality for interference-aware wireless sensor networks. ACM SIGBED Review 8(4), 43–48 (2011)
Doddavenkatappa, M., Chan, M.C., Leong, B.: Improving link quality by exploiting channel diversity in wireless sensor networks. In: IEEE RTSS 2011, pp. 159–169 (2011)
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Iyer, V., Hermans, F., Voigt, T. (2015). Detecting and Avoiding Multiple Sources of Interference in the 2.4 GHz Spectrum. In: Abdelzaher, T., Pereira, N., Tovar, E. (eds) Wireless Sensor Networks. EWSN 2015. Lecture Notes in Computer Science, vol 8965. Springer, Cham. https://doi.org/10.1007/978-3-319-15582-1_3
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DOI: https://doi.org/10.1007/978-3-319-15582-1_3
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