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Experimental Challenges in Wireless Sensor Networks — Environment, Mobility, and Interference
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Computer Systems. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems. (Communication Research)
2012 (English)Doctoral thesis, comprehensive summary (Other academic)
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.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2012. , 156 p.
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 965
Keyword [en]
Wireless Sensor Networks, Testbed, Mobility, Interference classification
National Category
Computer Sciences Communication Systems
Research subject
Computer Science with specialization in Computer Communication
Identifiers
URN: urn:nbn:se:uu:diva-179807ISBN: 978-91-554-8448-4 (print)OAI: oai:DiVA.org:uu-179807DiVA: diva2:546335
Public defence
2012-10-12, Polhemsalen, Ångströmlaboratoriet, Lägerhyddsvägen 1, Uppsala, 13:15 (English)
Opponent
Supervisors
Projects
WISENET
Funder
Vinnova, P26628-4
Available from: 2012-09-20 Created: 2012-08-23 Last updated: 2018-01-12
List of papers
1. Vendetta – A Tool for Flexible Monitoring and Management of Distributed Testbeds
Open this publication in new window or tab >>Vendetta – A Tool for Flexible Monitoring and Management of Distributed Testbeds
2007 (English)In: Proc. 3rd International Conference on Testbeds and Research Infrastructure for the Development of Networks and Communities, Piscataway, NJ: IEEE , 2007, 8- p.Conference paper, Published paper (Refereed)
Place, publisher, year, edition, pages
Piscataway, NJ: IEEE, 2007
National Category
Information Systems
Research subject
Computer Science with specialization in Computer Communication
Identifiers
urn:nbn:se:uu:diva-21354 (URN)10.1109/TRIDENTCOM.2007.4444683 (DOI)978-1-4244-0739-2 (ISBN)
Conference
TridentCom 2007
Available from: 2006-12-19 Created: 2006-12-19 Last updated: 2018-01-12Bibliographically approved
2. Sensei-UU: a relocatable sensor network testbed
Open this publication in new window or tab >>Sensei-UU: a relocatable sensor network testbed
2010 (English)In: Proc. 5th ACM International Workshop on Wireless Network Testbeds, Experimental Evaluation and Characterization, ACM Press, 2010, 63-70 p.Conference paper, Published paper (Refereed)
Place, publisher, year, edition, pages
ACM Press, 2010
Keyword
heterogeneity, mobility, testbed, wireless sensor networks
National Category
Computer Engineering Communication Systems
Research subject
Computer Science with specialization in Computer Communication
Identifiers
urn:nbn:se:uu:diva-136397 (URN)10.1145/1860079.1860091 (DOI)
Projects
WISENETProFuN
Available from: 2010-12-13 Created: 2010-12-13 Last updated: 2018-01-12Bibliographically approved
3. Repeatable experiments with mobile nodes in a relocatable WSN testbed
Open this publication in new window or tab >>Repeatable experiments with mobile nodes in a relocatable WSN testbed
Show others...
2011 (English)In: Computer journal, ISSN 0010-4620, E-ISSN 1460-2067, Vol. 54, no 12, 1973-1986 p.Article in journal (Refereed) Published
Abstract [en]

Many sensor network application scenarios include mobile nodes, such as a moving sink. Evaluatingsuch applications in a testbed is challenging since the testbed has to support mobile nodes. Wepresent Sensei-UU, a sensor network testbed that supports mobile sensor nodes. The testbedis inexpensive, relocatable and possible to reproduce by other researchers. Its primary designobjectives are to support experiments with repeatable mobility and to support relocating thetestbed deployment to different locations. Mobile sensor nodes are carried by robots that usefloor markings for navigation and localization. The testbed can be used to evaluate applicationsin which sensor nodes move in the order of meters rather than millimeters, e.g., when a humancarries a mobile phone that collects data while passing stationary sensor nodes. To investigate therepeatability of robot movements, we measure the achieved precision and timing of the robots, andfind that our robot localization is accurate to ±1 cm. Furthermore, we investigate variations inradio signal strengths between mobile and stationary nodes. We study the impact of imprecisemovements, external sources of interference, and environmental influences. We conclude thatSensei-UU supports experiments in which these variations are acceptably low to capture small-scalefading phenomena in IEEE 802.15.4.

National Category
Computer Engineering Signal Processing
Research subject
Computer Science with specialization in Computer Communication; Electrical Engineering with specialization in Signal Processing
Identifiers
urn:nbn:se:uu:diva-151814 (URN)10.1093/comjnl/bxr052 (DOI)000298386300005 ()
Projects
WISENETProFuN
Available from: 2011-04-18 Created: 2011-04-18 Last updated: 2018-01-12Bibliographically approved
4. A Lightweight Approach to Online Detection and Classification of Interference in 802.15.4-based Sensor Networks
Open this publication in new window or tab >>A Lightweight Approach to Online Detection and Classification of Interference in 802.15.4-based Sensor Networks
2012 (English)In: ACM SIGBED Review, ISSN 1551-3688, Vol. 9, no 3, 11-20 p.Article in journal (Refereed) 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.

National Category
Computer Engineering Communication Systems
Identifiers
urn:nbn:se:uu:diva-179803 (URN)10.1145/2367580.2367582 (DOI)
Conference
3rd International Workshop on Networks of Cooperating Objects (CONET 2012)
Projects
WISENET
Available from: 2012-08-23 Created: 2012-08-23 Last updated: 2018-01-12Bibliographically approved
5. SoNIC: Classifying and Surviving Interference in 802.15.4-based Sensor Networks
Open this publication in new window or tab >>SoNIC: Classifying and Surviving Interference in 802.15.4-based Sensor Networks
Show others...
2012 (English)Report (Other academic)
Series
Technical report / Department of Information Technology, Uppsala University, ISSN 1404-3203 ; 2012-022
National Category
Computer Engineering
Identifiers
urn:nbn:se:uu:diva-179804 (URN)
Projects
WISENET
Available from: 2012-08-23 Created: 2012-08-23 Last updated: 2018-01-12Bibliographically approved

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