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dc.contributor.authorTsioliaridou, A.en
dc.contributor.authorLiaskos, Christos K.en
dc.contributor.authorIoannidis, S.en
dc.contributor.authorPitsillides, Andreasen
dc.creatorTsioliaridou, A.en
dc.creatorLiaskos, Christos K.en
dc.creatorIoannidis, S.en
dc.creatorPitsillides, Andreasen
dc.description.abstractA nanonetwork comprises a high number of autonomous nodes with wireless connectivity, assembled at micro-to-nanoscale. In general, manufacturing and cost considerations imply that nanonetworking approaches should have minimal complexity, ideally without sacrifices in network coverage. The present paper studies a networking approach fit for static, dense topologies comprising numerous, identical, computationally-constrained nodes. These attributes are especially important in the context of recently proposed applications of nanonetworks. The presented networking approach assumes that each node is equipped with 10 bits of reclaimable storage to accommodate four integer counters, and a trivial set of integer operations on them. These modest resources are used for logging packet reception statistics. Nanonodes with good reception serve as retransmitters within the network. This classification process is based on the Misra-Gries algorithm, used for detecting frequent items into sequential streams. Evaluation via extensive simulations in various 2D and 3D topologies yields high network coverage, achieved with less resources than related approaches. © 2015 Elsevier B.V..en
dc.sourceNano Communication Networksen
dc.subjectWireless networksen
dc.subjectComplex networksen
dc.subjectLow complexityen
dc.subjectNano scaleen
dc.subjectDigital storageen
dc.subjectExtensive simulationsen
dc.subjectNetwork coverageen
dc.subjectData disseminationen
dc.subjectClassification processen
dc.subjectDense topologiesen
dc.subjectInteger operationsen
dc.subjectWireless connectivitiesen
dc.titleLightweight, self-tuning data dissemination for dense nanonetworksen
dc.description.endingpage15 Σχολή Θετικών και Εφαρμοσμένων Επιστημών / Faculty of Pure and Applied SciencesΤμήμα Πληροφορικής / Department of Computer Science
dc.source.abbreviationNano Commun.Netw.en
dc.contributor.orcidPitsillides, Andreas [0000-0001-5072-2851]

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