# Traffic Profiling for Mobile Video Streaming

## TL;DR

This paper introduces a non-intrusive, real-time traffic profiling system that estimates key HTTP Adaptive Streaming parameters using only IP-layer data, even with encrypted traffic, aiding network optimization.

## Contribution

A novel traffic profiling method that observes IP flows at network edges to infer application-layer parameters without requiring standardization or decryption.

## Key findings

- High accuracy in estimating streaming parameters
- Works with encrypted TLS traffic
- Effective for network optimization

## Abstract

This paper describes a novel system that provides key parameters of HTTP Adaptive Streaming (HAS) sessions to the lower layers of the protocol stack. A non-intrusive traffic profiling solution is proposed that observes packet flows at the transmit queue of base stations, edge-routers, or gateways. By analyzing IP flows in real time, the presented scheme identifies different phases of an HAS session and estimates important application-layer parameters, such as play-back buffer state and video encoding rate. The introduced estimators only use IP-layer information, do not require standardization and work even with traffic that is encrypted via Transport Layer Security (TLS). Experimental results for a popular video streaming service clearly verify the high accuracy of the proposed solution. Traffic profiling, thus, provides a valuable alternative to cross-layer signaling and Deep Packet Inspection (DPI) in order to perform efficient network optimization for video streaming.