Perturbation Analysis and On-Line Control: for Discrete Event Systems via Stochastic Fluid Models

Sun, Gang

ISBN 10: 3639131797 / ISBN 13: 9783639131796

Verlag: VDM Verlag Dr. Müller, 2009

Beschreibung

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Bestandsnummer des Verkäufers ERICA75836391317976

Bibliografische Details

• Titel: Perturbation Analysis and On-Line Control: for Discrete Event Systems via Stochastic Fluid Models
• Verlag: VDM Verlag Dr. Müller
• Erscheinungsjahr: 2009
• Sprache: Englisch
• ISBN-10: 3639131797
• ISBN-13: 9783639131796
• Einband: Paperback
• Zustand: Like New
• Buchtyp: book

Über diesen Titel

Inhaltsangabe

The application area that motivates this dissertation Is e?cient resource allocation and control in communication networks with Quality of service (QoS) requirements.Though a natural modelling framework of packet-based networks is provided through discrete-event systems, classical queueing theory becomes impractical to deal with the huge volume of events of high-speed networks with di?erent levels of service. In this dissertation,we use Stochastic Fluid Models(SFM)for control and optimization (rather than performance analysis)of communication networks nodes, ,focusing on problems of bu?er control.Solving such problems can often make use of gradient information.Perturbation Analysis(PA) methods are therefore suitable if appropriately adapted to SFMs.In this dissertation we show that In?nitesimal Perturbation Analysis (IPA) yields simple sensitivity estimators for packet loss and workload related performance metrics with respect to various control parameters.These estimator are shown to be unbiased and directly observable from a sample path without any knowledge of underlying stochastic characteristics of the traffic process.

Reseña del editor

The application area that motivates this dissertation Is efficient resource allocation and control in communication networks with Quality of service (QoS) requirements.Though a natural modelling framework of packet-based networks is provided through discrete-event systems, classical queueing theory becomes impractical to deal with the huge volume of events of high-speed networks with different levels of service. In this dissertation,we use Stochastic Fluid Models(SFM)for control and optimization (rather than performance analysis)of communication networks nodes, ,focusing on problems of buffer control.Solving such problems can often make use of gradient information.Perturbation Analysis(PA) methods are therefore suitable if appropriately adapted to SFMs.In this dissertation we show that Infinitesimal Perturbation Analysis (IPA) yields simple sensitivity estimators for packet loss and workload related performance metrics with respect to various control parameters.These estimator are shown to be unbiased and directly observable from a sample path without any knowledge of underlying stochastic characteristics of the traffic process.