Approximate Online Learning for Passive Monitoring of Multi-channel Wireless Networks

We consider the problem of optimally assigning $p$ sniffers to $K$ channels to monitor the transmission activities in a multi-channel wireless network. The activity of users is initially unknown to the sniffers and is to be learned along with channel assignment decisions. Previously proposed online learning algorithms face high computational costs due to the NP-hardness of the decision problem. In this paper, we propose two approximate online …