Predicting cluster formation in decentralized sensor grids

Astrid Zeman*, Mikhail Prokopenko

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

Abstract

This paper investigates cluster formation in decentralized sensor grids and focusses on predicting when the cluster formation converges to a stable configuration. The traffic volume of inter-agent communications is used, as the underlying time series, to construct a predictor of the convergence time. The predictor is based on the assumption that decentralized cluster formation creates multiagent chaotic dynamics in the communication space, and estimates irregularity of the communication-volume time series during an initial transient interval. The new predictor, based on the auto-correlation function, is contrasted with the predictor based on the correlation entropy (generalized entropy rate). In terms of predictive power, the auto-correlation function is observed to outperform and be less sensitive to noise in the communication space than the correlation entropy. In addition, the preference of the auto-correlation function over the correlation entropy is found to depend on the synchronous message monitoring method.

Original languageEnglish
Title of host publicationKnowledge-Based Intelligent Information and Engineering Systems - 10th International Conference, KES 2006, Proceedings
Place of PublicationBerlin; Heidelberg
PublisherSpringer, Springer Nature
Pages324-332
Number of pages9
Volume4253 LNAI - III
ISBN (Print)3540465421, 9783540465423
Publication statusPublished - 2006
Externally publishedYes
Event10th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2006 - Bournemouth, United Kingdom
Duration: 9 Oct 200611 Oct 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4253 LNAI - III
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other10th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2006
CountryUnited Kingdom
CityBournemouth
Period9/10/0611/10/06

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