A correction was published on 26 October 2011, see Sensors 2011, 11(11), 10165.

Sensors 2011, 11(8), 8180-8202; doi:10.3390/s110808180
Article

LinkMind: Link Optimization in Swarming Mobile Sensor Networks

1 The More-Than-One Robotics lab, Department of Electronic Systems, Automation and Control Section, Aalborg University, Fredik Bajers Vej 7C, 9220 Aalborg, Denmark 2 Faculty of Science, National University of Brunei, Jln Tungku, BE1410, Brunei
Received: 13 June 2011; in revised form: 12 August 2011 / Accepted: 15 August 2011 / Published: 23 August 2011
(This article belongs to the Special Issue Bioinspired Sensor Systems)
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Abstract: A swarming mobile sensor network is comprised of a swarm of wirelessly connected mobile robots equipped with various sensors. Such a network can be applied in an uncertain environment for services such as cooperative navigation and exploration, object identification and information gathering. One of the most advantageous properties of the swarming wireless sensor network is that mobile nodes can work cooperatively to organize an ad-hoc network and optimize the network link capacity to maximize the transmission of gathered data from a source to a target. This paper describes a new method of link optimization of swarming mobile sensor networks. The new method is based on combination of the artificial potential force guaranteeing connectivities of the mobile sensor nodes and the max-flow min-cut theorem of graph theory ensuring optimization of the network link capacity. The developed algorithm is demonstrated and evaluated in simulation.
Keywords: optimization; max-flow min-cut; robot swarms; sensor network; line-of-sight communication

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MDPI and ACS Style

Ngo, T.D. LinkMind: Link Optimization in Swarming Mobile Sensor Networks. Sensors 2011, 11, 8180-8202.

AMA Style

Ngo TD. LinkMind: Link Optimization in Swarming Mobile Sensor Networks. Sensors. 2011; 11(8):8180-8202.

Chicago/Turabian Style

Ngo, Trung Dung. 2011. "LinkMind: Link Optimization in Swarming Mobile Sensor Networks." Sensors 11, no. 8: 8180-8202.

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