Crowdsensing Approach to Monitoring and Optimize Wi-Fi Networks in Adversarial Environments

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Abstract
The signal quality of Wi-Fi networks tends to decrease in settings with high client density, bad Access Point (AP) coverage, or radio interferences from the presence of rogue APs (RAPs). This work proposes a novel solution for monitoring of the Wi-Fi network through a crowdsensing approach, combining data collected from user devices and fixed monitoring nodes. The developed system assesses Wi-Fi signal quality, detects and assails rogue APs, assesses the number of clients per area and the RAPs impact on the signal surrounding them. The system, tested on a large faculty building with over 1,000 Wi-Fi users, proved to be efficient, simple to use and adaptable, being easily deployed in any large and multi-floored building and network.