Please use this identifier to cite or link to this item:
https://ruomo.lib.uom.gr/handle/7000/1509
Title: | Correlation-based wireless sensor networks performance: the compressed sensing paradigm |
Authors: | Xifilidis, Theofanis Psannis, Kostas E. |
Type: | Article |
Subjects: | FRASCATI::Engineering and technology FRASCATI::Natural sciences |
Keywords: | Compressed Sensing correlation error Wireless Sensor Networks |
Issue Date: | 2022 |
Source: | Cluster Computing |
Volume: | 25 |
Issue: | 2 |
First Page: | 965 |
Last Page: | 981 |
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. |
URI: | https://doi.org/10.1007/s10586-021-03480-4 https://ruomo.lib.uom.gr/handle/7000/1509 |
ISSN: | 1386-7857 1573-7543 |
Other Identifiers: | 10.1007/s10586-021-03480-4 |
Appears in Collections: | Department of Applied Informatics |
Files in This Item:
File | Description | Size | Format | |
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PAPER SPRINGER CLUSTER COMPUTING FINAL.pdf | Paper final submitted version | 832,06 kB | Adobe PDF | View/Open |
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