2008 Poster Sessions : Optimal Scheduling of Media Packets with Multiple Distortion Measures

Student Name : Carri Chan
Advisor : Nicholas Bambos
Research Areas: Information Systems
Due to the increase in different wireless devices, streaming media systems must be capable of serving multiple types of users.
Scalable coding allows for adaptations without re-encoding. To account for various viewing capabilities of each user, multiple distortion measures are used. In this paper, we examine the question of how to broadcast media packets with multiple distortion measures to multiple users. We begin by presenting an offline algorithm to generate the optimal transmission policy in a general case. We then show that the optimal policy can be done online via a simple threshold policy in the case of independent Bernoulli packet losses. Through experimental results, we show that our policy, which considers multiple distortion measures, achieves up to 2dB gains over conventional approaches.

Carri Chan is a PhD student in the Information Systems Lab at Stanford University. Her research interests are focused on performance engineering and stochastic optimization in networked systems. Recent work has been on problems related to packet scheduling for multimedia transmission over wireless networks.