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Energy efficient monitoring of water distribution networks via compressive sensing
KTH, School of Electrical Engineering (EES), Automatic Control.ORCID iD: 0000-0002-1934-9208
KTH, School of Electrical Engineering (EES), Automatic Control.
KTH, School of Electrical Engineering (EES), Automatic Control.ORCID iD: 0000-0001-9810-3478
KTH, School of Electrical Engineering (EES), Communication Theory. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0002-5407-0835
2015 (English)In: 2015 IEEE International Conference on Communications (ICC), IEEE conference proceedings, 2015, Vol. 2015, 6681-6686 p.Conference paper, Published paper (Refereed)
Abstract [en]

The recent development of low cost wireless sensors enables water monitoring through dense wireless sensor networks (WSN). Sensor nodes are battery powered devices, and hence their limited energy resources have to be optimally managed. The latest advancements in compressive sensing (CS) provide ample promise to increase WSNs lifetime by limiting the amount of measurements that have to be collected. Additional energy savings can be achieved through CS-based scheduling schemes that activate only a limited number of sensors to sense and transmit their measurements, whereas the rest are turned off. The ultimate objective is to maximize network lifetime without sacrificing network connectivity and monitoring performance. This problem can be approximated by an energy balancing approach that consists of multiple simpler subproblems, each of which corresponds to a specific time period. Then, the sensors that should be activated within a given period can be optimally derived through dynamic programming. The complexity of the proposed CS-based scheduling scheme is characterized and numerical evaluation reveals that it achieves comparable monitoring performance by activating only a fraction of the sensors.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2015. Vol. 2015, 6681-6686 p.
Series
IEEE International Conference on Communications, ISSN 1550-3607
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-165840DOI: 10.1109/ICC.2015.7249390ISI: 000371708106148Scopus ID: 2-s2.0-84953790048ISBN: 978-1-4673-6432-4 (print)OAI: oai:DiVA.org:kth-165840DiVA: diva2:808906
Conference
IEEE International Conference on Communications, ICC 2015, London, United Kingdom, 8 June 2015 through 12 June 2015
Note

QC 20151104

Available from: 2015-04-29 Created: 2015-04-29 Last updated: 2016-04-21Bibliographically approved

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Du, RongFischione, CarloXiao, Ming

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