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Welcome to the Center for Wireless Communications at the University of California, San Diego. CWC was established in 1995 and rapidly became a leader in wireless communications research. With its preeminent faculty and high caliber graduate students, CWC partners with companies to address the emerging needs of the wireless communications industry. CWC faculty and students engage in a broad range of research areas ranging from wireless applications, to networking, digital communication systems and high-speed integrated circuits.
Events
Designing Optimal Resource Sharing in the Long Run
Wednesday, January 22, 2014
Mihaela van der Schaar
Host: Professor Tara Javidi
Abstract
The problem of resource sharing is ubiquitous: transceivers need to share the scarce wireless spectrum; traffic flows need to share routers’ available bandwidth; applications and tasks need to share the central processing units (CPUs) and memory of computer systems; consumer appliances need to share the available energy supply etc. A key feature of all such resource sharing problems is that the use of the resource by a single agent (e.g. a user, a transceiver, an application) has a negative effect on the usage of other agents sharing the same resource. Existing state-of-the-art solutions to this problem are generally inefficient, require extensive and perfect feedback and monitoring, and most of the time cannot cope with dynamic entry and exit or self-interested users.
In this talk, I will propose a novel, systematic and practical design framework for distributed resource sharing that is optimal (efficient), decentralized, requires minimal and imperfect feedback and monitoring, allows for dynamic entry and exit and for self-interested agents. (That is, agents – who may be heterogeneous, who are autonomous and who maximize their own payoffs subject to constraints such as minimum throughput requirements, maximum energy consumption constraints, delay constraints, etc.). We model the problem as a stochastic game among agents with conflicting objectives and coupled constraints. A crucial and necessary feature of our solutions –optimal policies – is that they are nonstationary: each agent’s action depends not only on its current state but also on the history of previous states and actions. Our solution provides a novel and rigorous methodology to determine optimal spectrum sharing policies that flexibly optimize the desired system performance in terms of throughput, energy consumption, delay or utility-based fairness. Our preliminary results show that, in comparison with the state-of-the-art solutions, our proposed solutions improve the total throughput by as much as 300% or reduce the energy consumption by 80-90%.
The proposed optimal resource sharing methodology can be used for a variety of other systems such as video over Internet-of-Things enabled networks, smart grids, cloud computing, crowdsourcing etc. [More...]
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