Characterizing user behavior and network performance in a public wireless LAN
SIGMETRICS '02 Proceedings of the 2002 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
The changing usage of a mature campus-wide wireless network
Proceedings of the 10th annual international conference on Mobile computing and networking
A scalable framework for wireless network monitoring
Proceedings of the 2nd ACM international workshop on Wireless mobile applications and services on WLAN hotspots
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
Map: a scalable monitoring system for dependable 802.11 wireless networks
IEEE Wireless Communications
Manipulating Wi-Fi packet traces with WiPal: design and experience
Software—Practice & Experience
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Existing measurement techniques for IEEE~802.11-based networks assume that the higher the density of monitors in the target area, the higher the quality of the measure. This assumption is, however, too strict if we consider the cost involved in monitor installation and the necessary time to collect and merge all traces. In this paper, we investigate the balance between number of traces and completeness of collected data. We propose a method based on similarity to rank collected traces according to their contribution to the monitoring system. With this method, we are able to select only a subset of traces and still keep the quality of the measure, while improving system scalability. In addition, based on the same rank, we identify monitors that can be relocated to enlarge the monitored area and increase the overall efficiency of the system. Finally, our experimental results show that the proposed solution leads to a better tradeoff in terms of unique captured frames over the number of merge operations.