Unobtrusive, Pervasive, and Cost-Effective Communications with Mobile Device

Mobile devices such as smartphones are ubiquitous in society. According to Cisco Systems, there were eight billion mobile devices worldwide in 2016, which surpassed the human population. Mobile devices and wireless network infrastructure form an "electronic world" of signals that is part of daily life. However, navigating this world with users' devices is challenging. The volume of signals may confuse users, wireless communications often require manual connection establishment, and latency may be large (such as Bluetooth device discovery). Pervasive mobile device communications offer large-scale measurement opportunities when many devices connect to wireless networks. For example, base stations to which devices connect can indicate human mobility patterns. But existing work only studies coarse-grained cellular call records and datasets used in wireless local area network (WLAN) studies typically consist of laptops. Besides, existing vehicular communications technologies tend to be expensive and available for new vehicles only.;This dissertation studies three topics that arise in the electronic world: unobtrusive communication among mobile devices without manual connection establishment; pervasive mobile device communications measurement; and cost-effective vehicular communication among mobile devices. First, we design Enclave that enables unobtrusive communication among mobile devices without network connections or configurations. Unobtrusive communication is efficient wireless communication that does not require user interruption such as manual device connection or network configuration. Enclave consists of a delegate mobile device (such as an unused phone) that interposes between a user's "master" device (such as her smartphone) and the electronic world. Enclave communicates between the master and delegate devices using wireless name communication and picture communication. Second, we study a new dataset with over 41 million anonymized (dis)association logs with WLAN access points (APs) at The Ohio State University (via the osuwireless network) over 139 days from January to May 2015. The dataset includes more than 5,000 university students with their birthdays, genders, and majors, which are made available after anonymization. Using mobility entropy as our metric, we find that entropy increases with age (for 19-21-year-olds), students' entropic rates of change vary with majors, and all students' long-term entropy follows a bimodal distribution that has not been previously reported. We design a mobile application that localizes users indoors for 73 campus buildings using WLAN site survey information. In general, our app achieves room-level accuracy. Finally, we propose SquawkComm for cost-effective vehicular communication using mobile devices and FM signals. SquawkComm encodes data as audio, which is sent via inexpensive FM transmitters that plug into vehicles' cigarette lighters and received via vehicle stereos. SquawkComm uses a new physical-layer coding scheme and link-layer mechanisms for channel access. Our experimental evaluation illustrates the promise of our work in the electronic world. We conclude with directions for future work.