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Condizione: New. pp. 286 1st edition NO-PA16APR2015-KAP.
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Aggiungi al carrelloCondizione: Hervorragend. Zustand: Hervorragend | Seiten: 302 | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.
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Aggiungi al carrelloPaperback. Condizione: Brand New. 302 pages. 9.21x6.14x0.79 inches. In Stock.
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Large Scale Networks | Modeling and Simulation | Radu Dobrescu (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2020 | CRC Press | EAN 9780367655891 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.
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Aggiungi al carrelloCondizione: buono. Fotografia Fine arts Photography BUONE CONDIZIONI Volume in lingua romena - in 4°.
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Aggiungi al carrelloCouverture rigide. Condizione: bon. RO30359328: 1976. In-4. Relié. Bon état, Coins frottés, Dos satisfaisant, Papier jauni. Environ 500 pages. Quelques rousseurs. Signet conservé. Jaquette passable. Nombreuses planches de photos et illustrations en noir et blanc et en couleurs. Avec Jaquette. . . Classification Dewey : 947-Europe de l'Est, URSS.
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book offers a rigorous analysis of the achievements in the field of traffic control in large networks, oriented on two main aspects: the self-similarity in traffic behaviour and the scale-free characteristic of a complex network. Additionally, the authors propose a new insight in understanding the inner nature of things, and the cause-and-effect based on the identification of relationships and behaviours within a model, which is based on the study of the influence of the topological characteristics of a network upon the traffic behaviour. The effects of this influence are then discussed in order to find new solutions for traffic monitoring and diagnosis and also for traffic anomalies prediction. Although these concepts are illustrated using highly accurate, highly aggregated packet traces collected on backbone Internet links, the results of the analysis can be applied for any complex network whose traffic processes exhibit asymptotic self-similarity, perceived as an adaptability of traffic in networks. However, the problem with self-similar models is that they are computationally complex. Their fitting procedure is very time-consuming, while their parameters cannot be estimated based on the on-line measurements. In this aim, the main objective of this book is to discuss the problem of traffic prediction in the presence of self-similarity and particularly to offer a possibility to forecast future traffic variations and to predict network performance as precisely as possible, based on the measured traffic history. 304 pp. Englisch.
Da: Biblios, Frankfurt am main, HESSE, Germania
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Aggiungi al carrelloCondizione: New. PRINT ON DEMAND pp. 286.
Da: moluna, Greven, Germania
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Aggiungi al carrelloCondizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Radu Dobrescu was born in 1946. He received his Dipl.Eng. degree in Automatic Control from the Faculty of Control and Computers of the Polytechnical Institute of Bucharest in 1968. In 1976, he received his Ph.D. degree in Automatic Contr.
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 106,33
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book offers a rigorous analysis of the achievements in the field of traffic control in large networks, oriented on two main aspects: the self-similarity in traffic behaviour and the scale-free characteristic of a complex network. Additionally, the authors propose a new insight in understanding the inner nature of things, and the cause-and-effect based on the identification of relationships and behaviours within a model, which is based on the study of the influence of the topological characteristics of a network upon the traffic behaviour. The effects of this influence are then discussed in order to find new solutions for traffic monitoring and diagnosis and also for traffic anomalies prediction. Although these concepts are illustrated using highly accurate, highly aggregated packet traces collected on backbone Internet links, the results of the analysis can be applied for any complex network whose traffic processes exhibit asymptotic self-similarity, perceived as an adaptability of traffic in networks. However, the problem with self-similar models is that they are computationally complex. Their fitting procedure is very time-consuming, while their parameters cannot be estimated based on the on-line measurements. In this aim, the main objective of this book is to discuss the problem of traffic prediction in the presence of self-similarity and particularly to offer a possibility to forecast future traffic variations and to predict network performance as precisely as possible, based on the measured traffic history.