Networked devices and systems currently operate in a passive manner that limits both the individual and the overall network/system performance. Specifically, they try to maximize their immediate utility by myopically optimizing their operation, without trying to forecast the impact of their actions on the future utilities, or to proactively influence the long-term network/system dynamics.

In this talk, we propose to fundamentally change the passive way in which devices currently interact, by enabling them to proactively compete for the dynamic resources and improve their performances, based on their information, learning capabilities and available actions. Specifically, we introduce a new networking and computing paradigm, where devices compete in various centralized and decentralized resource .markets. regulated by users, network providers, or system managers, aiming to maximize their own utilities or the social welfare. To model and design various resource markets, we propose a general stochastic game formulation. When operating in such resource markets, devices become selfish, autonomous users, who strategically interact in order to acquire the necessary resources for optimizing their performance, given the experienced network, system, and application dynamics. The actions selected by the devices for playing the stochastic game are the cross-layer algorithms and parameters that can be adopted at the various layers of the protocol stack or system layers. To be able to make foresighted and proactive decisions, users will need to learn and model directly or indirectly the other users. responses to their actions. We study the outcome of various dynamic interactions among strategic users possessing different knowledge levels and actions, and show that the proposed paradigm can lead to multi-user systems that achieve new measures of optimality, rationality and fairness. Exemplary systems to which the proposed paradigm was already successfully applied include multi-user competitions in existing wireless network infrastructures, emerging cognitive radio networks, peer-to-peer networks and multi-task processing systems. Our results show that .smart. users, which are able to successfully learn, forecast, negotiate, interact and adapt, will not only be able to derive higher utilities, but also help to achieve unprecedented network or system efficiency improvements.

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Mihaela van der Schaar is currently an Associate Professor in the Electrical Engineering Department at UCLA. She received in 2004 the NSF Career Award, in 2005 the Best Paper Award from IEEE Transactions on Circuits and Systems for Video Technology, in 2006 the Okawa Foundation Award, in 2005 and 2007 the IBM Faculty Award, and in 2006 the Most Cited Paper Award from EURASIP: Image Communications journal. She holds 30 granted US patents and three ISO awards. Her research interests are in multimedia communications, networking, architectures, systems, compression and processing. For more information on her research, please visit http://medianetlab.ee.ucla.edu.