Extraction of nonredundant information from sensor networks
Authors:
- Zbigniew Kokosiński
Abstract
In this paper we present four new algorithms for solving Minimum Base Problem (MBP) which is known to be NP-complete. The problem arises in wide or dense sensor networks in which a huge number of sensors provides a highly redundant source of information and should be reduced for further processing. In many cases a proper selection of nonredundant subset of the set of all sensors is reasonable both from economical point of view and the computational complexity of processing vast input data by software or hardware. Both exact and approximate algorithms are to be developed and applied for this task. In addition a hybrid metaheuristic are shown.
- Record ID
- CUT755928d73ca14bd9a7b20db296b53d37
- Publication categories
- ; ;
- Author
- Pages
- 403-407
- Other elements of collation
- wykr.; Bibliografia (na s.) - 407; Bibliografia (liczba pozycji) - 18; Oznaczenie streszczenia - Abstr.
- Substantive notes
- Data wyd. wg cop.
- Book
- IDAACS'2021 : proceedings of the 11th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS), September 22-25, 2021, Cracow, Poland : virtual conference. Vol. 1, Proceedings of the IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems, 2021, [Piscataway], Institute of Electrical and Electronics Engineers, IEEE, ISBN 978-1-6654-2605-3 (electronic)
- Keywords in English
- Minimum Base Problem (MBP), approximate algorithm, exact algorithm, wireless sensor network, Conferences, Software algorithms, metaheuristics, data acquisition, approximation algorithms, software, hardware
- DOI
- DOI:10.1109/IDAACS53288.2021.9660929 Opening in a new tab
- URL
- https://ieeexplore.ieee.org/document/9660929 Opening in a new tab
- Language
- eng (en) English
- Score (nominal)
- 20
- Publication indicators
- = 1
- Citation count
- 1
- Additional fields
- Indeksowana w: Web of Science, Scopus
- Uniform Resource Identifier
- https://cris.pk.edu.pl/info/article/CUT755928d73ca14bd9a7b20db296b53d37/
- URN
urn:pkr-prod:CUT755928d73ca14bd9a7b20db296b53d37
* presented citation count is obtained through Internet information analysis, and it is close to the number calculated by the Publish or PerishOpening in a new tab system.