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The Scientific World Journal
Volume 2015, Article ID 569841, 6 pages
http://dx.doi.org/10.1155/2015/569841
Research Article

Advanced Approach of Multiagent Based Buoy Communication

1Institute of Mathematics and Informatics, Vilnius University, Akademijos Street 4, 08663 Vilnius, Lithuania
2Department of Informatics Engineering, Faculty of Marine Engineering, Klaipeda University, Bijunu Street 17-206, 91225 Klaipeda, Lithuania
3Institute of Digital Technologies, Faculty of Social Technologies, Mykolas Romeris University, Ateities Street 20, 08303 Vilnius, Lithuania
4Department of Telecommunications, Faculty of Electrical Engineering and Computer Science, VSB-Technical University of Ostrava, 17. Listopadu 15, 708 00 Ostrava, Czech Republic

Received 27 August 2014; Accepted 10 October 2014

Academic Editor: Ivan Zelinka

Copyright © 2015 Gediminas Gricius et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Usually, a hydrometeorological information system is faced with great data flows, but the data levels are often excessive, depending on the observed region of the water. The paper presents advanced buoy communication technologies based on multiagent interaction and data exchange between several monitoring system nodes. The proposed management of buoy communication is based on a clustering algorithm, which enables the performance of the hydrometeorological information system to be enhanced. The experiment is based on the design and analysis of the inexpensive but reliable Baltic Sea autonomous monitoring network (buoys), which would be able to continuously monitor and collect temperature, waviness, and other required data. The proposed approach of multiagent based buoy communication enables all the data from the costal-based station to be monitored with limited transition speed by setting different tasks for the agent-based buoy system according to the clustering information.