IRES Track-I PILOT: Location-Independent Multi-Source Video Streaming

University Of Louisiana At Lafayette, Lafayette LA

Investigators

Abstract

Video streaming is the major source of Internet traffic in the U.S. and worldwide. To enable high quality and fast video streaming, independent from the viewers' geographical location, researchers propose to explore a inter-fog computing system called Latency Aware STreaming (LAST) that enables multi-source video streaming. Leveraging the locality feature exists in video stream requests, LAST will be able to partially pre-process video streams and stream the missing segments simultaneously from peer LASTs that possibly have those missing segments cached. LASTs also have the ability to locally process video streams. Therefore, for each video segment, a LAST has to determine whether to stream it from a neighboring LAST or process it locally. To reduce streaming latency further, the LAST platform proactively determines hot videos in a certain jurisdiction and preheats those videos at the fog level. This is an exploratory but potentially transformative research idea in its early stages. This project, involving the radical approach of multi-source video streaming, is considered high risk/ potentially high payoff. The project is interdisciplinary and combines cloud/fog computing and video streaming. To explore this idea, two students (possibly one graduate and one undergraduate student) are expected to travel to visit CLOUDS Lab at Melbourne University in Australia that is directed by Dr. Rajkumar Buyya, one of the most outstanding researchers in cloud computing and he is the highest cited scientist in Cloud Computing. In a close collaboration with CLOUDS lab, the team of researchers will learn working with iFogSim, which is a platform for simulating and testing fog computing systems developed at CLOUDS Lab. It will enable students to simulate and prototype the proposed LAST platform. During the visit, students will learn and extend iFogSim to accommodate video streaming tasks and achieve multi-source streaming via inter-fog systems. This project will help undergraduate and graduate students from UL Lafayette to become highly skilled and globally engaged workforce. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.