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Backbone formation in military multi-layer ad hoc networks using complex network concepts

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Auteur
Papakostas D., Basaras P., Katsaros D., Tassiulas L.
Date
2016
Language
en
DOI
10.1109/MILCOM.2016.7795434
Sujet
Ad hoc networks
Artificial intelligence
Complex networks
Decision support systems
Drones
Helicopters
Military communications
Military helicopters
Mobile telecommunication systems
Network layers
Network protocols
Spreaders
Unmanned aerial vehicles (UAV)
Ad-hoc communication
Back-bone network
Backbone formation
Connected Dominating Set
Efficient communications
Multi-layer network
Network backbones
Network-wide broadcasting
Vehicular ad hoc networks
Institute of Electrical and Electronics Engineers Inc.
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Résumé
Modern battlefields are characterized by increasing deployment of ad hoc communications among allied entities. These networks can be seen as a complex multi-layer ad hoc network, where each layer may be an independently acting soldiers' group, a group of drones, helicopters, vehicles and so on. Building a backbone network for these environments, which will guarantee efficient communication among all nodes (i.e., network-wide broadcasting) is of fundamental significance for the dissemination of information. In this article we generalize the concept of connected dominating sets for multi-layer networks and use them as the network backbone. We propose efficient methods to identify nodes that are efficient cross-layer spreaders along with a distributed algorithm to build the connected dominating set. Due to the lack of competing methods in the literature, we compare the proposed methods against some baseline methods and investigate the performance of all algorithms for a variety of multi-layer network topologies, illustrating their advantages and disadvantages; the result of the evaluation identifies the clPCI method of recognizing efficient cross-layer spreaders as the champion method. © 2016 IEEE.
URI
http://hdl.handle.net/11615/77740
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  • Δημοσιεύσεις σε περιοδικά, συνέδρια, κεφάλαια βιβλίων κλπ. [19735]

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