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Internet Service Providers (ISPs) are struggling to cope with the growing volume of streaming video traffic in their network, and the problem will only exacerbate as Virtual Reality applications proliferate. To classify and manage bandwidth for video streams, current practise is to either sample traffic for offline analysis or deploy middle-boxes for in-line packet inspection - such solutions are inaccurate and/or expensive. In this paper we present Telescope, a low-cost system comprising a commodity SDN switch and a commodity server, to identify and profile individual video flows at line-rate. We develop an architecture that dynamically manages flow-table entries to classify video flows with minimal mirroring of packets, we prototype our solution using a Noviflow OpenFlow switch, coupled with the Bro packet inspection engine and our application on a Ryu controller, lastly, we validate our solution with real video streams in a campus WiFi network, and test its scaling to thousands of video flows using a hardware-based traffic generator. We believe our solution offers great potential for real-time video classification in an operational network at very low cost.
Wang et al. (Sat,) studied this question.
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