NeTS: Small: Recovery and Transformation of Human Mobility Traces for Mobile Wireless Experimentation

NeTS：小型：移动无线实验的人体移动轨迹的恢复和转化

• 批准号: 1117190
• 负责人: Ellen Zegura
• 金额: $ 39.99万
• 依托单位: Georgia Tech Research Corporation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-08-01 至 2015-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1117190&HistoricalAwards=false
• 关键词: NeTS; Small; Recovery; Transformation; Human

The advent of cheap, ubiquitous, portable, multi-radio devices means that mobile wireless networking will be the predominant future method for network access and edge network formation. Many of these devices will have mobility that is dictated by the movement of the humans who carry them. Hence, capturing real-world human mobility patterns is essential for improving our understanding of the new networks and communication opportunities that will arise. However, even small-scale measurements carry a significant organizational overhead in preparing, distributing and collecting contact loggers, not to mention non-technical issues related to legality and participant consent. This research program addresses two key issues: the recovery of mobility information from contact traces, and the transformation of traces collected under one set of circumstances to realistic alternative scenarios. The basis for the recovery work is a dynamic, force-based heuristic to recover plausible mobility from a contact trace. The basis for the transformation techniques is the combination of the original trace and the plausible mobility, plus models for real-world alternative settings. In both cases, the work addresses fundamental questions about efficient computational methods and the limits to computational capability for recovery and transformation. Answers to these two questions will allow researchers to collect and transform traces so as to extract maximum value from expensive measurement methods, enabling trace-driven simulation of mobile wireless networks to play a central role beside analysis and direct experimentation. In addition, the trace collection experiments used in validation will provide a valuable resource to researchers in mobile networking.

廉价、无处不在、便携式、多无线电设备的出现意味着移动的无线联网将成为未来网络接入和边缘网络形成的主要方法。这些设备中的许多设备将具有由携带它们的人的移动决定的移动性。因此，捕捉真实世界的人类移动模式对于提高我们对新网络和即将出现的通信机会的理解至关重要。然而，即使是小规模的测量，在准备、分发和收集接触记录器方面也会产生重大的组织开销，更不用说与合法性和参与者同意有关的非技术问题了。该研究计划解决了两个关键问题：从接触痕迹中恢复移动信息，以及将在一组情况下收集的痕迹转换为现实的替代方案。恢复工作的基础是一个动态的，基于力的启发式恢复合理的流动性，从接触痕迹。转换技术的基础是原始轨迹和合理移动性的组合，以及现实世界替代设置的模型。在这两种情况下，工作解决了有关有效的计算方法和恢复和转换的计算能力的限制的基本问题。这两个问题的答案将使研究人员能够收集和转换痕迹，以便从昂贵的测量方法中提取最大价值，从而使移动的无线网络的痕迹驱动模拟在分析和直接实验之外发挥核心作用。此外，验证中使用的跟踪收集实验将为移动的网络研究人员提供宝贵的资源。