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Constraint Programming for Wireless Sensor Networks
Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för datalogi. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Datalogi. (ASTRA)
2015 (engelsk)Doktoravhandling, med artikler (Annet vitenskapelig)
Abstract [en]

In recent years, wireless sensor networks (WSNs) have grown rapidly and have had a substantial impact in many applications. A WSN is a network that consists of interconnected autonomous nodes that monitor physical and environmental conditions, such as temperature, humidity, pollution, etc. If required, nodes in a WSN can perform actions to affect the environment.

WSNs present an interesting and challenging field of research due to the distributed nature of the network and the limited resources of the nodes. It is necessary for a node in a WSN to be small to enable easy deployment in an environment and consume as little energy as possible to prolong its battery lifetime. There are many challenges in WSNs, such as programming a large number of nodes, designing communication protocols, achieving energy efficiency, respecting limited bandwidth, and operating with limited memory. WSNs are further constrained due to the deployment of the nodes in indoor and outdoor environments and obstacles in the environment.

In this dissertation, we study some of the fundamental optimisation problems related to the programming, coverage, mobility, data collection, and data loss of WSNs, modelled as standalone optimisation problems or as optimisation problems integrated with protocol design. Our proposed solution methods come from various fields of research including constraint programming, integer linear programming, heuristic-based algorithms, and data inference techniques.

sted, utgiver, år, opplag, sider
Uppsala: Acta Universitatis Upsaliensis, 2015. , s. 80
Serie
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 1219
Emneord [en]
Constraint programming, wireless sensor networks, optimisation, macroprogramming, task mapping
HSV kategori
Forskningsprogram
Datavetenskap med inriktning mot datorkommunikation
Identifikatorer
URN: urn:nbn:se:uu:diva-241378ISBN: 978-91-554-9144-4 (tryckt)OAI: oai:DiVA.org:uu-241378DiVA, id: diva2:778823
Disputas
2015-03-13, Room 2446, Polacksbacken, Lägerhyddsvägen 2, Uppsala, 13:00 (engelsk)
Opponent
Veileder
Prosjekter
ProFuNTilgjengelig fra: 2015-02-06 Laget: 2015-01-12 Sist oppdatert: 2018-01-11bibliografisk kontrollert
Delarbeid
1. Energy-efficient task mapping for data-driven sensor network macroprogramming using constraint programming
Åpne denne publikasjonen i ny fane eller vindu >>Energy-efficient task mapping for data-driven sensor network macroprogramming using constraint programming
2011 (engelsk)Inngår i: Operations Research, Computing, and Homeland Defense, Hanover, MD: Institute for Operations Research and the Management Sciences , 2011, s. 199-209Konferansepaper, Publicerat paper (Fagfellevurdert)
sted, utgiver, år, opplag, sider
Hanover, MD: Institute for Operations Research and the Management Sciences, 2011
HSV kategori
Identifikatorer
urn:nbn:se:uu:diva-136365 (URN)10.1287/ics.2011.0016 (DOI)978-0-9843378-1-1 (ISBN)
Konferanse
12th INFORMS Computing Society Conference
Prosjekter
ProFuN
Forskningsfinansiär
Swedish Foundation for Strategic Research , RIT08-0065
Tilgjengelig fra: 2011-01-11 Laget: 2010-12-12 Sist oppdatert: 2018-01-12bibliografisk kontrollert
2. An optimisation-based approach for wireless sensor deployment in mobile sensing environments
Åpne denne publikasjonen i ny fane eller vindu >>An optimisation-based approach for wireless sensor deployment in mobile sensing environments
2012 (engelsk)Inngår i: Proc. Wireless Communications and Networking Conference 2012, IEEE Communications Society, 2012, s. 2108-2112Konferansepaper, Publicerat paper (Fagfellevurdert)
sted, utgiver, år, opplag, sider
IEEE Communications Society, 2012
HSV kategori
Identifikatorer
urn:nbn:se:uu:diva-171536 (URN)10.1109/WCNC.2012.6214140 (DOI)000324580702038 ()978-1-4673-0436-8 (ISBN)
Konferanse
WCNC 2012
Prosjekter
ProFuN
Forskningsfinansiär
Swedish Foundation for Strategic Research , RIT08-0065
Tilgjengelig fra: 2012-06-11 Laget: 2012-03-20 Sist oppdatert: 2018-01-12bibliografisk kontrollert
3. Optimising quality of information in data collection for mobile sensor networks
Åpne denne publikasjonen i ny fane eller vindu >>Optimising quality of information in data collection for mobile sensor networks
2013 (engelsk)Inngår i: Proc. 21st International Symposium on Quality of Service, IEEE Communications Society, 2013, s. 163-172Konferansepaper, Publicerat paper (Fagfellevurdert)
sted, utgiver, år, opplag, sider
IEEE Communications Society, 2013
HSV kategori
Identifikatorer
urn:nbn:se:uu:diva-208996 (URN)10.1109/IWQoS.2013.6550277 (DOI)000325614100019 ()978-1-4799-0589-8 (ISBN)
Konferanse
IEEE/ACM 21st International Symposium on Quality of Service (IWQoS), 3-4 June, 2013, Montreal, QC
Prosjekter
ProFuN
Forskningsfinansiär
Swedish Foundation for Strategic Research , RIT08-0065
Tilgjengelig fra: 2013-10-13 Laget: 2013-10-13 Sist oppdatert: 2018-01-11bibliografisk kontrollert
4. A constraint programming approach for managing end-to-end requirements in sensor network macroprogramming
Åpne denne publikasjonen i ny fane eller vindu >>A constraint programming approach for managing end-to-end requirements in sensor network macroprogramming
Vise andre…
2014 (engelsk)Inngår i: Proc. 3rd International Conference on Sensor Networks / [ed] Postolache, Octavian; van Sinderen, Marten; Ali, Falah; Benavente-Peces, César, Setúbal, Portugal: SciTePress, 2014, s. 28-40Konferansepaper, Publicerat paper (Fagfellevurdert)
sted, utgiver, år, opplag, sider
Setúbal, Portugal: SciTePress, 2014
HSV kategori
Identifikatorer
urn:nbn:se:uu:diva-210431 (URN)10.5220/0004715200280040 (DOI)978-989-758-001-7 (ISBN)
Konferanse
SENSORNETS 2014
Prosjekter
ProFuN
Forskningsfinansiär
Swedish Foundation for Strategic Research , RIT08-0065
Tilgjengelig fra: 2014-01-09 Laget: 2013-11-08 Sist oppdatert: 2018-01-11bibliografisk kontrollert
5. Energy-efficient sensor selection for data quality and load balancing in wireless sensor networks
Åpne denne publikasjonen i ny fane eller vindu >>Energy-efficient sensor selection for data quality and load balancing in wireless sensor networks
2014 (engelsk)Inngår i: Proc. 22nd International Symposium on Quality of Service, IEEE Communications Society, 2014, s. 338-343Konferansepaper, Publicerat paper (Fagfellevurdert)
sted, utgiver, år, opplag, sider
IEEE Communications Society, 2014
HSV kategori
Identifikatorer
urn:nbn:se:uu:diva-229594 (URN)10.1109/IWQoS.2014.6914338 (DOI)000355927000044 ()978-1-4799-4852-9 (ISBN)
Konferanse
IWQoS 2014, May 26–27, Hong Kong, China
Prosjekter
ProFuN
Forskningsfinansiär
Swedish Foundation for Strategic Research , RIT08-0065
Tilgjengelig fra: 2014-05-27 Laget: 2014-08-11 Sist oppdatert: 2018-01-11bibliografisk kontrollert
6. Cloud-Assisted Data Fusion and Sensor Selection for Internet-of-Things
Åpne denne publikasjonen i ny fane eller vindu >>Cloud-Assisted Data Fusion and Sensor Selection for Internet-of-Things
(engelsk)Manuskript (preprint) (Annet vitenskapelig)
Abstract [en]

The Internet of Things (IoT) is connecting people and smart devices on a scale that once was unimaginable. One major challenge for the IoT is to handle vast amount of sensing data generated from the smart devices that are resource-limited and subject to missing data due to link or node failures. By exploring cloud computing with the IoT, we present a cloud-based solution that takes into account the link quality and spatio-temporal correlation of data to minimise energy consumption by selecting sensors for sampling and relaying data. We propose a multi-phase adaptive sensing algorithm with belief propagation protocol (ASBP), which can provide high data quality and reduce energy consumption by turning on only a small number of nodes in the network. We formulate the sensor selection problem and solve it using constraint programming (CP) and greedy search. We then use our message passing algorithm (belief propagation) for performing inference to reconstruct the missing sensing data. ASBP is evaluated based on the data collected from real sensors. The results show that while maintaining a satisfactory level of data quality and prediction accuracy, ASBP can provide load balancing among sensors successfully and preserves 80\% more energy compared with the case where all sensor nodes are actively involved.

HSV kategori
Forskningsprogram
Datavetenskap
Identifikatorer
urn:nbn:se:uu:diva-241377 (URN)
Prosjekter
ProFuN
Tilgjengelig fra: 2015-01-12 Laget: 2015-01-12 Sist oppdatert: 2018-01-11

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