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

廉价、无处不在、便携式、多无线电设备的出现意味着移动无线联网将成为未来网络接入和边缘网络形成的主要方式。这些设备中的许多将具有由携带它们的人的移动所决定的移动性。因此，捕捉真实世界的人类流动模式对于提高我们对即将出现的新网络和通信机会的理解至关重要。然而，即使是小规模的测量也会在准备、分发和收集联系人记录器方面带来巨大的组织开销，更不用说与合法性和参与者同意相关的非技术问题了。这项研究计划解决两个关键问题：从联系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。恢复工作的基础是动态的、基于力的启发式方法，以从接触痕迹恢复合理的移动性。转换技术的基础是原始轨迹和看似合理的移动性的结合，以及现实世界中替代设置的模型。在这两种情况下，这项工作都解决了关于有效的计算方法以及恢复和转换的计算能力的限制的基本问题。对这两个问题的回答将允许研究人员收集和转换痕迹，以便从昂贵的测量方法中提取最大价值，使移动无线网络的轨迹驱动模拟在分析和直接实验之外发挥核心作用。此外，用于验证的痕迹收集实验将为移动网络研究人员提供宝贵的资源。

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.