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A Particle Swarm Mobility Model for Flying Ad Hoc Networks

机译:用于飞行Ad Hoc网络的粒子群移动模型

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Flying Ad hoc Network (FANET) is a special type of Mobile Ad hoc Network (MANET), which is a collection of UAVs (Unmanned Aerial Vehicles) forming a self- configuring network without using any existing infrastructure. Since FANETs are not currently deployed on a large scale, research in this area is mostly simulation based. The mobility model plays a fundamental role in constructing simulation environment for enabling upper layer research. Existing mobility models mostly target general MANETs, and they are unable to capture the unique features of fast moving UAVs in the context of FANETs. In this paper, we propose a group mobility model called Particle Swarm Mobility Model (PSMM) based on particle swarming for FANETs. The distinct feature of PSMM is that it can mimic the UAV swarm movement with a simple computational framework. It captures both the temporal correlation of a UAV itself as well as the spatial correlation across multiple UAVs that are flying as a coordinated group. We validate the effectiveness of PSMM using a set of relevant metrics. The experimental results show that PSMM meets these metrics well and can provide a solid infrastructure for simulation-based FANET research.
机译:飞行ad hoc网络(FANET)是一种特殊类型的移动临时网络(MANET),它是在不使用任何现有基础架构的情况下形成自配置网络的无人机(无人机航空车辆)的集合。由于粉丝目前没有大规模部署,因此该区域的研究主要是基于仿真的。移动模型在构建仿真环境方面发挥着基本作用,以实现上层研究。现有的移动性模型主要是针对普通船只,他们无法在粉丝的上下文中捕获快速移动的无人机的独特功能。在本文中,我们提出了一种基于粉丝的粒子蜂拥而至的粒子群移动模型(PSMM)的组移动模型。 PSMM的独特特征是它可以模仿与简单的计算框架的无人机群运动。它捕获了UAV本身的时间相关性以及跨飞行作为协调组的多个无人机的空间相关性。我们使用一组相关指标验证PSMM的有效性。实验结果表明,PSMM符合这些指标良好,可以为基于仿真的粉丝研究提供稳固的基础设施。

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