NeTS: Small: MobiBench: Benchmarking Mobility Models for Simulation and Design of Future Networks

NeTS：小型：MobiBench：未来网络仿真和设计的基准移动模型

• 批准号: 1320694
• 负责人: Ahmed Helmy
• 金额: $ 37.75万
• 依托单位: University of Florida
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-10-01 至 2019-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1320694&HistoricalAwards=false
• 关键词: NeTS; Small; MobiBench; Benchmarking; Mobility

With the explosion of new mobile apps, protocols and services, there is a compelling need for new tools to evaluate and test mobile networks. This project aims to establish a systematic framework to produce benchmarks (called MobiBench) in the form of evaluation scenarios and test-suites for mobile networking protocols and services for user and vehicular mobility. Two threads of research are pursued. First, a multi-dimensional metric space is introduced for characterization of user (human) mobility, to be applied to mobility measurements and models. The metrics span: i. individual, ii. pair-wise and iii. collective mobility dimensions, and facilitate comprehensive analysis and evaluation of mobility models and networking protocols. Novel, trace-driven models are developed to accurately capture user mobility metrics and mobile network performance. The COBRA model is designed to capture collective communal behavior in mobile social networks. Second, new extensive vehicular traces are collected and analyzed, including vehicular imagery data from thousands of webcams around the world. Vehicular density distributions and models are developed to aid in establishing realistic vehicular mobility models and benchmarks. Estimation of vehicular density uses adapted background subtraction algorithms for image processing. This work will result in the establishment of a library of benchmarks, traces, models and test-suites for pedestrian and vehicular mobility, to be used for the realistic evaluation of future mobile protocols, networks and services. Results of this research will impact mobile networking research and aid in traffic control and transportation congestion mitigation.

随着新的移动的应用程序、协议和服务的激增，迫切需要新的工具来评估和测试移动的网络。该项目旨在建立一个系统框架，以评估方案和测试套件的形式为用户和车辆的移动性提供移动的网络协议和服务，从而产生基准（称为基准测试）。研究的两个线索进行。首先，一个多维的度量空间引入用户（人）的移动性的表征，应用到移动性测量和模型。度量跨度：个人，二。成对的和iii.集体移动性维度，并促进移动性模型和网络协议的综合分析和评估。新颖的，跟踪驱动的模型，准确地捕捉用户的移动性指标和移动的网络性能。COBRA模型旨在捕捉移动的社交网络中的集体公共行为。其次，收集和分析新的广泛的车辆痕迹，包括来自世界各地数千个网络摄像头的车辆图像数据。车辆密度分布和模型的开发，以帮助建立现实的车辆流动性模型和基准。车辆密度的估计使用用于图像处理的自适应背景减除算法。这项工作将导致建立一个关于行人和车辆流动性的基准、轨迹、模型和测试套件库，用于对未来的移动的协议、网络和服务进行现实的评估。这项研究的结果将影响移动的网络研究，并有助于交通控制和交通拥堵缓解。