uu.seUppsala University Publications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Cloud-Assisted Data Fusion and Sensor Selection for Internet-of-Things
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science. (ASTRA)
(English)Manuscript (preprint) (Other academic)
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.

National Category
Computer Sciences
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:uu:diva-241377OAI: oai:DiVA.org:uu-241377DiVA, id: diva2:778822
Projects
ProFuNAvailable from: 2015-01-12 Created: 2015-01-12 Last updated: 2018-01-11
In thesis
1. Constraint Programming for Wireless Sensor Networks
Open this publication in new window or tab >>Constraint Programming for Wireless Sensor Networks
2015 (English)Doctoral thesis, comprehensive summary (Other academic)
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.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2015. p. 80
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 1219
Keywords
Constraint programming, wireless sensor networks, optimisation, macroprogramming, task mapping
National Category
Computer Sciences
Research subject
Computer Science with specialization in Computer Communication
Identifiers
urn:nbn:se:uu:diva-241378 (URN)978-91-554-9144-4 (ISBN)
Public defence
2015-03-13, Room 2446, Polacksbacken, Lägerhyddsvägen 2, Uppsala, 13:00 (English)
Opponent
Supervisors
Projects
ProFuN
Available from: 2015-02-06 Created: 2015-01-12 Last updated: 2018-01-11Bibliographically approved

Open Access in DiVA

No full text in DiVA

Authority records BETA

Hassani Bijarbooneh, Farshid

Search in DiVA

By author/editor
Hassani Bijarbooneh, Farshid
By organisation
Computing Science
Computer Sciences

Search outside of DiVA

GoogleGoogle Scholar

urn-nbn

Altmetric score

urn-nbn
Total: 2265 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf