AirLab: consistency, fidelity and privacy in wireless measurements

Accurate measurements of deployed wireless networks are vital for researchers to perform realistic evaluation of proposed systems. Unfortunately, the difficulty of performing detailed measurements limits the consistency in parameters and methodology of current datasets. Using different datasets, multiple research studies can arrive at conflicting conclusions about the performance of wireless systems. Correcting this situation requires consistent and comparable wireless traces collected from a variety of deployment environments. In this paper, we describe AirLab, a distributed wireless data collection infrastructure that uses uniformly instrumented measurement nodes at heterogeneous locations to collect consistent traces of both standardized and user-defined experiments. We identify four challenges in the AirLab platform, consistency, fidelity, privacy, security, and describe our approaches to address them.

对部署的无线网络的准确测量对于研究人员对拟议系统进行现实评估至关重要。不幸的是，执行详细测量的困难限制了当前数据集的参数和方法的一致性。使用不同的数据集，多项研究可以得出有关无线系统性能的矛盾结论。纠正这种情况需要从各种部署环境中收集的一致和可比较的无线痕迹。在本文中，我们描述了Airlab，这是一种分布式无线数据收集基础架构，该基础结构在异质位置使用均匀的仪器测量节点，以收集标准化和用户定义的实验的一致轨迹。我们确定了Airlab平台，一致性，忠诚，隐私，安全性的四个挑战，并描述了我们解决这些问题的方法。