A Smooth-turn Mobility Model for Airborne Networks

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In this article, I introduce a novel airborne network mobility model, called the Smooth Turn Mobility Model, that captures the correlation of acceleration for airborne vehicles across time and spatial coordinates. E?ective routing in airborne networks (ANs) relies on suitable mobility models that capture the random movement pattern of airborne vehicles. As airborne vehicles cannot make sharp turns as easily as ground vehicles do, the widely used mobility models for Mobile Ad Hoc Networks such as Random Waypoint and Random Direction models fail. Our model is realistic in capturing the tendency of airborne vehicles toward making straight trajectory and smooth ... continued below

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He, Dayin August 2012.

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This thesis is part of the collection entitled: UNT Theses and Dissertations and was provided by UNT Libraries to Digital Library, a digital repository hosted by the UNT Libraries. It has been viewed 551 times , with 4 in the last month . More information about this thesis can be viewed below.

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  • He, Dayin

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In this article, I introduce a novel airborne network mobility model, called the Smooth Turn Mobility Model, that captures the correlation of acceleration for airborne vehicles across time and spatial coordinates. E?ective routing in airborne networks (ANs) relies on suitable mobility models that capture the random movement pattern of airborne vehicles. As airborne vehicles cannot make sharp turns as easily as ground vehicles do, the widely used mobility models for Mobile Ad Hoc Networks such as Random Waypoint and Random Direction models fail. Our model is realistic in capturing the tendency of airborne vehicles toward making straight trajectory and smooth turns with large radius, and whereas is simple enough for tractable connectivity analysis and routing design.

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  • August 2012

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  • March 4, 2013, 2:02 p.m.

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  • Nov. 16, 2016, 3:48 p.m.

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He, Dayin. A Smooth-turn Mobility Model for Airborne Networks, thesis, August 2012; Denton, Texas. (digital.library.unt.edu/ark:/67531/metadc149603/: accessed February 24, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; .