Network Utility Maximization with Temporal Variations and Storage
Professor Gustavo de Veciana
User perceived video quality depends on a variety of only partially understood factors, e.g., the application domain, content, compression, transport mechanism, and most importantly psycho-visual systems determining the ultimate Quality of Experience (QoE) of users. This talk centers on two key observations in addressing the problem of joint rate adaptation for video streams sharing a congested resource. First, we note that a user viewing a given video will experience temporal variations in the dependence of perceived video quality to the compression rate. Intuitively this is due to the possibly changing nature of the content, e.g., from an action to a slower scene. Thus, in allocating rates to users sharing a congested resource, in particular a wireless system where additional temporal variability in users’ capacity may be high, content dependent tradeoffs can be realized to deliver a better overall average perceived video quality. Second, we note that such adaptation of users’ rates, may result in temporal variations in video quality which combined with perceptual hysteresis effects will degrade users’ QoE. We develop an asymptotically optimal online algorithm, requiring minimal statistical information, for optimizing users’ QoE by realizing tradeoffs across mean, variance and fairness. Simulations show that our approach achieves significant gains in viewers’ QoE.
The theoretical novelty of this work lies in tackling a new class of temporally varying network utility maximization problem which can leverage storage. The practical aim is to achieve fair allocations of perceived video quality across a user population with time varying sensitivities and capacity, while integrating the deleterious impact that variations in perceived quality has on their QoE.
This is joint work with V. Joseph and Z. Lu and colleagues funded as part of the CISCO/INTEL Video Aware Wireless Networking research program.
Gustavo de Veciana received his B.S., M.S, and Ph.D. in electrical engineering from the University of California at Berkeley in 1987, 1990, and 1993 respectively, and joined the Department of Electrical and Computer Engineering where he is currently a Cullen Trust Professor of Engineering. He served as the Director and AssociateDirector of the Wireless Networking and Communications Group (WNCG) at the University of Texas at Austin, from 2003-2007. His research focuses on the analysis and design of wireless and wireline telecommunication networks; architectures and protocols to support sensing and pervasive computing; applied probability and queueing theory. Dr. de Veciana served as editor and is currently serving as editor-at-large for the IEEE/ACM Transactions on Networking. He was the recipient of a National Science Foundation CAREER Award 1996 and a co-recipient of five best paper awards including: IEEE William McCalla Best ICCAD Paper Award for 2000, Best Paper in ACM TODAES Jan 2002-2004, Best Paper in ITC 2010, Best Paper in ACM MSWIM 2010, and Best Paper IEEE INFOCOM 2014. In 2009 he was designated IEEE Fellow for his contributions to the analysis and design of communication networks. He is on the technical advisory board of IMDEA Networks.