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https://ruomo.lib.uom.gr/handle/7000/1509
Πλήρης εγγραφή μεταδεδομένων
Πεδίο DC | Τιμή | Γλώσσα |
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dc.contributor.author | Xifilidis, Theofanis | - |
dc.contributor.author | Psannis, Kostas E. | - |
dc.date.accessioned | 2022-10-18T11:19:28Z | - |
dc.date.available | 2022-10-18T11:19:28Z | - |
dc.date.issued | 2022 | - |
dc.identifier | 10.1007/s10586-021-03480-4 | en_US |
dc.identifier.issn | 1386-7857 | en_US |
dc.identifier.issn | 1573-7543 | en_US |
dc.identifier.uri | https://doi.org/10.1007/s10586-021-03480-4 | en_US |
dc.identifier.uri | https://ruomo.lib.uom.gr/handle/7000/1509 | - |
dc.description.abstract | In this paper, the performance of Wireless Sensor Networks (WSNs) operating for environmental monitoring is investigated. The performance metrics considered are normalized reconstruction error and energy estimation error. The temporal, spatial and spatiotemporal correlations are separately considered for the above metrics. The independent case and correlated cases for dense measurement cases along with the Compressed Sensing (CS) compressibility rule by selecting a subset of measurements for metric evaluation are thoroughly examined with extensive simulations and technical interpretations. Finally, applications of the proposed scheme are formulated in terms of topology and routing in fifth generation sensor networks and Internet of Things (IoT) deployment scenarios. | en_US |
dc.language.iso | en | en_US |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 International | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.source | Cluster Computing | en_US |
dc.subject | FRASCATI::Engineering and technology | en_US |
dc.subject | FRASCATI::Natural sciences | en_US |
dc.subject.other | Compressed Sensing | en_US |
dc.subject.other | correlation | en_US |
dc.subject.other | error | en_US |
dc.subject.other | Wireless Sensor Networks | en_US |
dc.title | Correlation-based wireless sensor networks performance: the compressed sensing paradigm | en_US |
dc.type | Article | en_US |
dc.contributor.department | Τμήμα Εφαρμοσμένης Πληροφορικής | en_US |
local.identifier.volume | 25 | en_US |
local.identifier.issue | 2 | en_US |
local.identifier.firstpage | 965 | en_US |
local.identifier.lastpage | 981 | en_US |
Εμφανίζεται στις Συλλογές: | Τμήμα Εφαρμοσμένης Πληροφορικής |
Αρχεία σε αυτό το Τεκμήριο:
Αρχείο | Περιγραφή | Μέγεθος | Μορφότυπος | |
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PAPER SPRINGER CLUSTER COMPUTING FINAL.pdf | Paper final submitted version | 832,06 kB | Adobe PDF | Προβολή/Ανοιγμα |
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