Intelligent System of Limited Resource Allocation for Large-Scale Agent Systems

Jakub Węcławski , Stanisław Jankowski


This paper describes an intelligent decision support system for semi-autonomous agents. The solution is developed for a large-scale network of double-interface mobile routers. The network is a part of advanced metering infrastructure deployed in the north of Poland. Limited capacity of cellular networks makes the system stability and performance dependent on smart management of radio resource utilization. A model of system phenomena was based on observations of a real system consisting of more than 10,000 devices. A network simulator was developed as a tool for solution testing outside of the real system. Computational Intelligence methods were found suitable for a large system scale. The paper introduces an iterative method based on cellular neural network model for determining the optimal resource allocation for the system.
Author Jakub Węcławski (FEIT / PE)
Jakub Węcławski,,
- The Institute of Electronic Systems
, Stanisław Jankowski (FEIT / PE)
Stanisław Jankowski,,
- The Institute of Electronic Systems
Publication size in sheets0.7
Book Ryżko Dominik Paweł, Gawrysiak Piotr, Kryszkiewicz Marzena, Rybiński Henryk (eds.): Machine Intelligence and Big Data in Industry, Studies in Big Data, vol. 19, 2016, Springer International Publishing Switzerland, ISBN 978-3-319-30314-7, [978-3-319-30315-4], 236 p., DOI:10.1007/978-3-319-30315-4
front matter.pdf / 82.6 KB / No licence information
Keywords in EnglishIntelligent decision support systems Computational intelligence Cellular neural network Advanced metering infrastructure Smart grid
ProjectResearch on measurement, circuit and signal theory and electronic circuits and systems. Project leader: Romaniuk Ryszard, , Phone: +48 22 234 7986, +48 22 234 5360, start date 15-06-2015, end date 31-12-2016, ISE/2015/DS, Completed
WEiTI Działalność statutowa
Languageen angielski
Score (nominal)0
Score sourcejournalList
ScoreMinisterial score = 0.0, 02-02-2020, BookChapterSeriesAndMatConfByIndicator
Ministerial score (2013-2016) = 0.0, 02-02-2020, BookChapterSeriesAndMatConfByIndicator
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