Bio-Inspired Topology Control Mechanism for Unmanned Underwater Vehicles View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2016

AUTHORS

Jianmin Zou , Stephen Gundry , M. Umit Uyar , Janusz Kusyk , Cem Safak Sahin

ABSTRACT

Unmanned underwater vehicles (uuvs) are increasingly used in maritime applications to acquire information in harsh and inaccessible underwater environments. uuvs can autonomously run intelligent topology control algorithms to adjust their positions such that they can achieve desired underwater wireless sensor network (uwsn) configurations. We present a topology control mechanism based on particle swarm optimization (pso), called 3d-pso, allowing uuvs to cooperatively protect valued assets in unknown 3d underwater spaces. 3d-pso provides a user-defined level of protection density around an asset and fault tolerant connectivity within the uwsn by utilizing Yao-graph inspired metrics in fitness calculations. Using only a limited information collected from a uuv’s neighborhood, 3d-pso guides uuvs to make movement decisions over unknown 3d spaces. Three classes of applications for uwsn configurations are presented and analyzed. In 3d encapsulation class of applications, uuvs uniformly cover the underside of a maritime vessel. In planar distribution class of applications, uuvs form a plane to cover a given dimension in 3d space. The third class involves spherical distribution of uuvs such that they are uniformly distributed and maintain connectivity. Formal analysis and experimental results with respect to average protection space, total underwater movement, average network connectivity and fault tolerance demonstrate that 3d-pso is an efficient tool to guide uuvs for these three classes of applications in uwsns. More... »

PAGES

727-752

Book

TITLE

Recent Advances in Computational Intelligence in Defense and Security

ISBN

978-3-319-26448-6
978-3-319-26450-9

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-319-26450-9_26

DOI

http://dx.doi.org/10.1007/978-3-319-26450-9_26

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1025875460


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