Wireless Communications: Principles and Practice
Wireless Communications: Principles and Practice
SenSay: A Context-Aware Mobile Phone
ISWC '03 Proceedings of the 7th IEEE International Symposium on Wearable Computers
Measurement driven deployment of a two-tier urban mesh access network
Proceedings of the 4th international conference on Mobile systems, applications and services
Surface street traffic estimation
Proceedings of the 5th international conference on Mobile systems, applications and services
Supporting vehicular mobility in urban multi-hop wireless networks
Proceedings of the 6th international conference on Mobile systems, applications, and services
Experiences in a 3G network: interplay between the wireless channel and applications
Proceedings of the 14th ACM international conference on Mobile computing and networking
Energy consumption in mobile phones: a measurement study and implications for network applications
Proceedings of the 9th ACM SIGCOMM conference on Internet measurement conference
Planet-scale human mobility measurement
Proceedings of the 2nd ACM International Workshop on Hot Topics in Planet-scale Measurement
Cuckoo: towards decentralized, socio-aware online microblogging services and data measurements
Proceedings of the 2nd ACM International Workshop on Hot Topics in Planet-scale Measurement
The challenges in large-scale smartphone user studies
Proceedings of the 2nd ACM International Workshop on Hot Topics in Planet-scale Measurement
A survey of mobile phone sensing
IEEE Communications Magazine
Improving wireless network performance using sensor hints
Proceedings of the 8th USENIX conference on Networked systems design and implementation
System architecture of a wireless body area sensor network for ubiquitous health monitoring
Journal of Mobile Multimedia
Relative location estimation in wireless sensor networks
IEEE Transactions on Signal Processing
Extrapolating sparse large-scale GPS traces for contact evaluation
Proceedings of the 5th ACM workshop on HotPlanet
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Mobile phones are becoming a powerful platform for global-scale measurements due to their ever-increasing programmability and prevalence. Moreover, advanced sensing capabilities have allowed mobile phones to become aware of the user's context, potentially leading to performance improvement. Such context awareness could be exploited to optimize a wireless network connection since wireless channels are known to depend on the surrounding environment. The viability of context-aware wireless performance improvement would heavily depend on whether differences in context had meaningful performance distinction and whether the training overhead per context encountered would overwhelm potential gains. In this paper, we perform a large-scale measurement study of regional performance based on a users context and characterize user mobility around the world. To do so, we deployed WiEye, an Android-based wireless sniffer which has collected over 50 million measurements from over 30 thousand unique users. We categorize measurements according to land use and political divisions to investigate whether distinct levels of performance exist as indicated by wireless path loss. We then examine user mobility patterns via subtractive fuzzy clustering to determine how many different contexts a user typically encounters. Our results show promise for context awareness since distinct levels of performance are observed per land use class with only one or two contexts being typical per user.