Modeling Communication over Terrain for Realistic Simulation of Outdoor Sensor Network Deployments

IF 0.7 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS ACM Transactions on Modeling and Performance Evaluation of Computing Systems Pub Date : 2021-12-31 DOI:10.1145/3510306
Sam Mansfield, K. Veenstra, K. Obraczka
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引用次数: 1

Abstract

Popular wireless network simulators have few available propagation models for outdoor Internet of Things applications. Of the available models, only a handful use real terrain data, yet an inaccurate propagation model can skew the results of simulations. In this article, we present TerrainLOS, a low-overhead propagation model for outdoor Internet of Things applications that uses real terrain data to determine whether two nodes can communicate. To the best of our knowledge, TerrainLOS is the first terrain-aware propagation model that specifically targets outdoor IoT deployments and that uses height maps to represent terrain. In addition, we present a new terrain classification method based on terrain “roughness,” which allows us to select a variety of terrain samples to demonstrate how TerrainLOS can capture the effects of terrain on communication. We also propose a technique to generate synthetic terrain samples based on “roughness.” Furthermore, we implemented TerrainLOS in the COOJA-Contiki network simulation/emulation platform, which targets IoT deployments and uses TerrainLOS to evaluate how often a network is fully connected based on the roughness of terrain, as well as how two popular power-aware routing protocols, RPL and ORPL, perform when terrain is considered.
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用于户外传感器网络部署真实仿真的地形通信建模
目前流行的无线网络模拟器很少有可用于户外物联网应用的传播模型。在现有的模型中,只有少数使用真实地形数据,而不准确的传播模型可能会影响模拟结果。在本文中,我们提出了TerrainLOS,这是一种用于户外物联网应用的低开销传播模型,它使用真实地形数据来确定两个节点是否可以通信。据我们所知,TerrainLOS是第一个专门针对室外物联网部署的地形感知传播模型,并使用高度图来表示地形。此外,我们提出了一种基于地形“粗糙度”的新的地形分类方法,这使我们能够选择各种地形样本来演示TerrainLOS如何捕捉地形对通信的影响。我们还提出了一种基于“粗糙度”生成合成地形样本的技术。此外,我们在COOJA-Contiki网络仿真/仿真平台中实现了TerrainLOS,该平台针对物联网部署,并使用TerrainLOS来评估基于地形粗糙度的网络完全连接的频率,以及考虑地形时两种流行的功率感知路由协议RPL和ORPL的执行情况。
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CiteScore
2.10
自引率
0.00%
发文量
9
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