The hundreds of millions of deployed smartphones provide an unprecedented opportunity to collect data to monitor, debug, and continuously adapt wireless networks to improve performance. In contrast with previous mobile devices, such as laptops, smartphones are always on but mostly idle, making them available to perform measurements that help other nearby active devices make better use of available network resources. We present the design of PocketSniffer, a system delivering wireless measurements from smartphones both to network administrators for monitoring and debugging purposes and to algorithms performing realtime network adaptation. By collecting data from smartphones, PocketSniffer supports novel adaptation algorithms designed around common deployment scenarios involving both cooperative and self-interested clients and networks. We present preliminary results from a prototype and discuss challenges to realizing this vision.
While smartphone app marketplaces have enabled large-scale app-level experimentation, medium-scale experimentation with the platform code implementing the app interface and providing core device services remains difficult for academic researchers. But this is where many of the ideas currently being explored by the mobile systems community must be evaluated---including new networking protocols, security and privacy mechanisms, storage abstractions, and energy management strategies. To enable these experiments, we built and are operating PhoneLab, a 175-smartphone testbed where real users run experimental Android platform builds on their primary devices. We are eager to make PhoneLab useful to the mobile systems community. To aid in this effort, this article discusses why PhoneLab might be useful for your research and provides an overview of how to use the testbed, including examples drawn from our group's current projects.
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