An accurate technique for measuring the wireless side of wireless networks
WiTMeMo '05 Papers presented at the 2005 workshop on Wireless traffic measurements and modeling
Measurement-based characterization of 802.11 in a hotspot setting
Proceedings of the 2005 ACM SIGCOMM workshop on Experimental approaches to wireless network design and analysis
Enhancing the security of corporate Wi-Fi networks using DAIR
Proceedings of the 4th international conference on Mobile systems, applications and services
Jigsaw: solving the puzzle of enterprise 802.11 analysis
Proceedings of the 2006 conference on Applications, technologies, architectures, and protocols for computer communications
Analyzing the MAC-level behavior of wireless networks in the wild
Proceedings of the 2006 conference on Applications, technologies, architectures, and protocols for computer communications
Understanding congestion in IEEE 802.11b wireless networks
IMC '05 Proceedings of the 5th ACM SIGCOMM conference on Internet Measurement
802.11 denial-of-service attacks: real vulnerabilities and practical solutions
SSYM'03 Proceedings of the 12th conference on USENIX Security Symposium - Volume 12
Automating cross-layer diagnosis of enterprise wireless networks
Proceedings of the 2007 conference on Applications, technologies, architectures, and protocols for computer communications
Active behavioral fingerprinting of wireless devices
WiSec '08 Proceedings of the first ACM conference on Wireless network security
A location-based management system for enterprise wireless LANs
NSDI'07 Proceedings of the 4th USENIX conference on Networked systems design & implementation
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The edge of the Internet is increasingly wireless. To understand the Internet, one must understand the edge, and yet the measurement of wireless networks poses many new challenges. IEEE 802.11 networks support multiple wireless channels and any monitoring technique involves capturing traffic on each of these channels to gather a representative sample of frames from the network. We call this procedure channel sampling, in which each sniffer visits each channel periodically, resulting in a sample of the traffic on each of the channels. This sampling approach may be sufficient, for example, for a system administrator or anomaly detection module to observe some unusual behavior in the network. Once an anomaly is detected, however, the administrator may require a more extensive traffic sample, or need to identify the location of an offending device. We propose a method to allow measurement applications to dynamically modify the sampling strategy, refocusing the monitoring system to pay more attention to certain types of traffic than others. In this paper we show that refocusing is a necessary and promising new technique for wireless measurement.