Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/80654
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dc.contributorDepartment of Industrial and Systems Engineering-
dc.creatorJiao, D-
dc.creatorKe, L-
dc.creatorLiu, S-
dc.creatorChan, FTS-
dc.date.accessioned2019-04-23T08:16:45Z-
dc.date.available2019-04-23T08:16:45Z-
dc.identifier.issn1424-8220en_US
dc.identifier.urihttp://hdl.handle.net/10397/80654-
dc.language.isoenen_US
dc.publisherMolecular Diversity Preservation International (MDPI)en_US
dc.rights© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).en_US
dc.rightsThe following publication Jiao, D., Ke, L., Liu, S., & Chan, F. T. (2019). Optimal Energy-Delay in Energy Harvesting Wireless Sensor Networks with Interference Channels. Sensors, 19(4), 785 is available at https://doi.org/10.3390/s19040785en_US
dc.subjectCapacity assignment problemen_US
dc.subjectConvex approximationen_US
dc.subjectEnergy harvestingen_US
dc.subjectEnergy transferen_US
dc.subjectInterference channelen_US
dc.subjectLagrange dualityen_US
dc.subjectWireless sensor networksen_US
dc.titleOptimal energy-delay in energy harvesting wireless sensor networks with interference channelsen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume19en_US
dc.identifier.issue4en_US
dc.identifier.doi10.3390/s19040785en_US
dcterms.abstractIn this work, we investigate the capacity allocation problem in the energy harvesting wireless sensor networks (WSNs) with interference channels. For the fixed topologies of data and energy, we formulate the optimization problem when the data flow remains constant on all data links and each sensor node harvests energy only once in a time slot. We focus on the optimal data rates, power allocations and energy transfers between sensor nodes in a time slot. Our goal is to minimize the total delay in the network under two scenarios, i.e., no energy transfer and energy transfer. Furthermore, since the optimization problem is non-convex and difficult to solve directly, by considering the network with the relatively high signal-to-interference-plus-noise ratio (SINR), the non-convex optimization problem can be transformed into a convex optimization problem by convex approximation. We attain the properties of the optimal solution by Lagrange duality and solve the convex optimization problem by the CVX solver. The experimental results demonstrate that the total delay of the energy harvesting WSNs with interference channels is more than that in the orthogonal channel; the total network delay increases with the increasing data flow for the fixed energy arrival rate; and the energy transfer can help to decrease the total delay.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationSensors (Switzerland), 2019, v. 19, no. 4, 785-
dcterms.isPartOfSensors (Switzerland)-
dcterms.issued2019-
dc.identifier.scopus2-s2.0-85061581654-
dc.identifier.pmid30769900-
dc.identifier.artn785en_US
dc.description.validate201904 bcmaen_US
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_IR/PIRAen_US
dc.description.pubStatusPublisheden_US
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