The amount of video content that is being distributed over the Internet is increasing. Video providers rely on HTTP adaptive streaming approaches to deliver video clips to users. Complementary to the video provider, the service provider must determine the priority of each network stream. As part of the project, students will explore wireless network assisted strategies for http adaptive streaming by use of TOS/DSCP. This includes using machine-learning tools to analyze network video traffic and the design of reinforcement learning algorithms to improve users' video Quality of Experience.

One selected candidate will receive a stipend via the DSI Scholars program. Amount is subject to available funding.

Faculty Advisor

Project Timeline

  • Earliest starting date: 3/1/2020
  • End date: 8/1/2020
  • Number of hours per week of research expected during Spring 2020: ~6
  • Number of hours per week of research expected during Summer 2020: ~40

Candidate requirements

  • Skill sets:
    • Understanding of networking and machine learning
    • Coding languages required include C, Java, and Python.
    • Knowledge of TOS/DSCP, openwrt, SDN, and mininet preferred.
    • Experience with programable networks, and SDN preferred.
  • Student eligibility: freshman, sophomore, junior, senior, master’s
  • International students on F1 or J1 visa: eligible