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A Lightweight Approach to Online Detection and Classification of Interference in 802.15.4-based Sensor Networks
Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Datorteknik. (Communication Research)
Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Datorteknik. (Communication Research)
Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Datorteknik. (Communication Research)
Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Datorteknik. (Communication Research)
2012 (Engelska)Ingår i: ACM SIGBED Review, ISSN 1551-3688, Vol. 9, nr 3, s. 11-20Artikel i tidskrift (Refereegranskat) Published
Abstract [en]

With a rapidly increasing number of devices sharing access to the 2.4 GHz ISM band, interference becomes a serious problem for 802.15.4-based, low-power sensor networks. Consequently, interference mitigation strategies are becoming commonplace. In this paper, we consider the step that precedes interference mitigation: interference detection. We have performed extensive measurements to characterize how different types of interferers affect individual 802.15.4 packets. From these measurements, we define a set of features which we use to train a neural network to classify the source of interference of a corrupted packet. Our approach is sufficiently lightweight for online use in a resource constrained sensor network. It does not require additional hardware, nor does it use active spectrum sensing or probing packets. Instead, all information about interferers is gathered from inspecting corrupted packets that are received during the sensor network’s regular operation. Even without considering a history of earlier packets, our approach reaches a mean classification accuracy of 79.8%, with per interferer accuracies of64.9% for WiFi, 82.6% for Bluetooth, 72.1% for microwave ovens, and 99.6% for packets that are corrupted due to insufficient signal strength.

Ort, förlag, år, upplaga, sidor
2012. Vol. 9, nr 3, s. 11-20
Nationell ämneskategori
Datorteknik Kommunikationssystem
Identifikatorer
URN: urn:nbn:se:uu:diva-179803DOI: 10.1145/2367580.2367582OAI: oai:DiVA.org:uu-179803DiVA, id: diva2:546307
Konferens
3rd International Workshop on Networks of Cooperating Objects (CONET 2012)
Projekt
WISENETTillgänglig från: 2012-08-23 Skapad: 2012-08-23 Senast uppdaterad: 2018-01-12Bibliografiskt granskad
Ingår i avhandling
1. Experimental Challenges in Wireless Sensor Networks — Environment, Mobility, and Interference
Öppna denna publikation i ny flik eller fönster >>Experimental Challenges in Wireless Sensor Networks — Environment, Mobility, and Interference
2012 (Engelska)Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
Abstract [en]

Wireless sensor networks are used to collect sensor data in different applications such as environmental monitoring, smart building control, and health care applications. Wireless sensor nodes used are typically small, low-cost, and battery powered. The nodes are often hard to access after deployment, for example when they are in remote  locations. Another property of wireless sensor networks is that their operation is dependent on the environment they operate in, both due to the specific sensor readings but also due to the effects on communication by factors such as fading and radio interference. This makes it important to evaluate a wireless sensor network in its intendent target environment before final deployment.

To enable experiments with wireless sensor networks in their target environment, we have designed and implemented a testbed called Sensei-UU. It is designed to allow WSN experiments to be repeated in different locations, thus exposing effects caused by the environment. To allow this, the testbed is designed to be easily moved between experimental sites.

One type of WSN applications Sensei-UU is aimed to evaluate is protocols where nodes are mobile. Mobile testbed nodes are low-cost robots which follow a tape track on the floor. The localization accuracy of the robot approach is evaluated and is accurate enough to expose a protocol to fading phenoma in a repeatable manner.

Sensei-UU has helped us develop a lightweight interference classification approach, SoNIC, which runs on standard motes. The approach only use information from a standard cc2420 chipset available when packets are received. We believe that the classification accuracy is good enough to motivate specific transmission techniques avoiding interference.

Ort, förlag, år, upplaga, sidor
Uppsala: Acta Universitatis Upsaliensis, 2012. s. 156
Serie
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 965
Nyckelord
Wireless Sensor Networks, Testbed, Mobility, Interference classification
Nationell ämneskategori
Datavetenskap (datalogi) Kommunikationssystem
Forskningsämne
Datavetenskap med inriktning mot datorkommunikation
Identifikatorer
urn:nbn:se:uu:diva-179807 (URN)978-91-554-8448-4 (ISBN)
Disputation
2012-10-12, Polhemsalen, Ångströmlaboratoriet, Lägerhyddsvägen 1, Uppsala, 13:15 (Engelska)
Opponent
Handledare
Projekt
WISENET
Forskningsfinansiär
Vinnova, P26628-4
Tillgänglig från: 2012-09-20 Skapad: 2012-08-23 Senast uppdaterad: 2018-01-12
2. Sensor Networks and Their Radio Environment: On Testbeds, Interference, and Broken Packets
Öppna denna publikation i ny flik eller fönster >>Sensor Networks and Their Radio Environment: On Testbeds, Interference, and Broken Packets
2014 (Engelska)Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
Abstract [en]

Sensor networks consist of small sensing devices that collaboratively fulfill a sensing task, such as monitoring the soil in an agricultural field or measuring vital signs in a marathon runner. To avoid cumbersome and expensive cabling, nodes in a sensor network are powered by batteries and communicate wirelessly. As a consequence of the latter, a sensor network's communication is affected by its radio environment, i.e., the environment's propagation characteristics and the presence of other radio devices. This thesis addresses three issues related to the impact of the radio environment on sensor networks.

Firstly, in order to draw conclusions from experimental results, it is necessary to assess how the environment and the experiment infrastructure affect the results. We design a sensor network testbed, dubbed Sensei-UU, to be easily relocatable. By performing an experiment in different environments, a researcher can asses the environments’ impact on results. We further augment Sensei-UU with support for mobile nodes. The implemented mobility approach adds only little variance to results, and therefore enables repeatable experiments with mobility. The repeatability of experiments increases the confidence in conclusions drawn from them.

Secondly, sensor networks may experience poor communication performance due to cross-technology radio interference, especially in office and residential environments. We consider the problem of detecting and classifying the type of interference a sensor network is exposed to. We find that different sources of interference each leave a characteristic "fingerprint" on individual, corrupt 802.15.4 packets. We design and implement the SoNIC system that enables sensor nodes to classify interference using these fingerprints. SoNIC supports accurate classification in both a controlled and an uncontrolled environment.

Finally, we consider transmission errors in an outdoor sensor network. In such an environment, errors occur despite the absence of interference if the signal-to-noise ratio at a receiver is too low. We study the characteristics of corrupt packets collected from an outdoor sensor network deployment. We find that content transformation in corrupt packets follows a specific pattern, and that most corrupt packets contain only few errors. We propose that the pattern may be useful for applications that can operate on inexact data, because it reduces the uncertainty associated with a corrupt packet.

Ort, förlag, år, upplaga, sidor
Uppsala: Acta Universitatis Upsaliensis, 2014. s. 73
Serie
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 1171
Nyckelord
Sensor networks, Testbed, Mobility, Interference classification, Packet corruption
Nationell ämneskategori
Kommunikationssystem
Forskningsämne
Datavetenskap med inriktning mot datorkommunikation
Identifikatorer
urn:nbn:se:uu:diva-230769 (URN)978-91-554-9019-5 (ISBN)
Disputation
2014-10-17, Room 1311, Polacksbacken, Lägerhyddsvägen 2, Uppsala, 13:00 (Engelska)
Opponent
Handledare
Projekt
WISENET
Forskningsfinansiär
VINNOVA, P26628-4
Tillgänglig från: 2014-09-24 Skapad: 2014-08-28 Senast uppdaterad: 2015-01-23

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