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UAV-Aided Projection-Based Compressive Data Gathering in Wireless Sensor Networks

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dc.contributor.author Ebrahimi, Dariush
dc.contributor.author Sharafeddine, Sanaa
dc.contributor.author Ho, Pin-Han
dc.contributor.author Assi, Chadi
dc.date.accessioned 2019-05-07T09:24:26Z
dc.date.available 2019-05-07T09:24:26Z
dc.date.copyright 2018 en_US
dc.identifier.issn 2327-4662 en_US
dc.identifier.uri http://hdl.handle.net/10725/10569
dc.description.abstract Fifth generation wireless networks are expected to provide advanced capabilities and create new markets. Among the emerging markets, Internet of Things (IoT) use cases are standing out with the proliferation of a wide range of sensors that can be configured to continuously monitor and transmit data for intelligent processing and decision making. Devices in such scenarios are normally extremely energy-constrained and often exist in large numbers and can be located in hard-to-reach areas; the fact that necessitates the design and implementation of effective energy-aware data collection mechanisms. To this end, we propose the utilization of Unmanned Aerial Vehicles (UAVs) to collect data in dense wireless sensor networks (WSNs) using projection-based Compressive Data Gathering (CDG) as a novel solution methodology. CDG is utilized to aggregate data en-route from a large set of sensor nodes to selected projection nodes acting as cluster heads in order to reduce the number of needed transmissions leading to notable energy savings and extended network lifetime. The UAV transfers the gathered data from the cluster heads to a remote sink node, e.g., a 5G cellular base station, which avoids the need for long range transmissions or multihop communications among the sensors. Our problem definition aims at clustering the sensors, constructing an optimized forwarding tree per cluster, and gathering the data from selected cluster head nodes based on projection-based CDG with minimized UAV trajectory distance. We formulate a joint optimization problem and divide it into four complementary subproblems to generate close-to-optimal results with lower complexity. Moreover, we propose a set of effective algorithms to generate solutions for relatively large-scale network scenarios. We demonstrate the superiority of the proposed approach and the designed algorithms via detailed performance results with analysis, comparisons and insights. en_US
dc.language.iso en en_US
dc.title UAV-Aided Projection-Based Compressive Data Gathering in Wireless Sensor Networks en_US
dc.type Article en_US
dc.description.version Published en_US
dc.author.school SAS en_US
dc.author.idnumber 200502746 en_US
dc.author.department Computer Science And Mathematics en_US
dc.description.embargo N/A en_US
dc.relation.journal IEEE Internet of Things Journal en_US
dc.journal.volume 6 en_US
dc.journal.issue 2 en_US
dc.article.pages 1893-1905 en_US
dc.keywords Sensors en_US
dc.keywords Wireless sensor networks en_US
dc.keywords Trajectory en_US
dc.keywords Data collection en_US
dc.keywords Energy consumption en_US
dc.keywords Unmanned aerial vehicles en_US
dc.keywords Compressed sensing en_US
dc.identifier.doi http://dx.doi.org/10.1109/JIOT.2018.2878834 en_US
dc.identifier.ctation Ebrahimi, D., Sharafeddine, S., Ho, P. H., & Assi, C. (2018). UAV-aided projection-based compressive data Gathering in wireless sensor networks. IEEE Internet of Things Journal, 6(2), 1893-1905. en_US
dc.author.email sanaa.sharafeddine@lau.edu.lb en_US
dc.identifier.tou http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php en_US
dc.identifier.url https://ieeexplore.ieee.org/abstract/document/8515012 en_US
dc.orcid.id https://orcid.org/0000-0001-6548-1624 en_US
dc.author.affiliation Lebanese American University en_US


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