This paper explores analytical Radio Resource Management models where the relationship between users and services is mapped through utility functions. Compared to other applications of these models to networking, we focus in particular on specific aspects of multimedia systems with adaptive traffic, and propose a novel framework for describing and investigating dynamic allocation of resources in wireless networks. In doing so, we also consider economic aspects, such as the financial needs of the provider and the users' reaction to prices. As an example of how our analytical tool can be used, in this paper we compare different classes of RRM strategies, e.g., Best Effort vs. Guaranteed Performance, for which we explore the relationships between Radio Resource Allocation, pricing, provider's revenue, network capacity and users' satisfaction. Finally, we present a discussion about Economic Admission Control, which can be applied in Best Effort scenarios to further improve the performance.

Dynamic utility and price based radio resource management for rate adaptive traffic

BADIA, LEONARDO;ZORZI, MICHELE
2008

Abstract

This paper explores analytical Radio Resource Management models where the relationship between users and services is mapped through utility functions. Compared to other applications of these models to networking, we focus in particular on specific aspects of multimedia systems with adaptive traffic, and propose a novel framework for describing and investigating dynamic allocation of resources in wireless networks. In doing so, we also consider economic aspects, such as the financial needs of the provider and the users' reaction to prices. As an example of how our analytical tool can be used, in this paper we compare different classes of RRM strategies, e.g., Best Effort vs. Guaranteed Performance, for which we explore the relationships between Radio Resource Allocation, pricing, provider's revenue, network capacity and users' satisfaction. Finally, we present a discussion about Economic Admission Control, which can be applied in Best Effort scenarios to further improve the performance.
2008
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/2444175
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