In recent years, growing processing power and bandwidth have stimulated a new breed of network applications requiring the development of more sophisticated traffic management algorithms to meet their stringent QoS needs. One of the main obstacles to improving QoS is congestion at network nodes. It is believe that bandwidth prediction is a key component to reducing congestion and thereby the improvement of QoS. This work proposes an effective bandwidth management approach based on the discrete wavelet transform (DWT). The approach hinges on the results of recent studies showing that while network traffic consists of both long- and short-term dependence, its wavelet coefficients are short-term dependent only. The DWT decomposes the traffic into a low-frequency component and high frequency components. The low- frequency component of the traffic, are significant for long-term traffic behavior and, hence, for bandwidth allocation. The high-frequency components are significant in the short-term behavior of the traffic and, hence, for buffer-allocation.
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In recent years, growing processing power and bandwidth have stimulated a new breed of network applications requiring the development of more sophisticated traffic management algorithms to meet their stringent QoS needs. One of the main obstacles to improving QoS is congestion at network nodes. It is believe that bandwidth prediction is a key component to reducing congestion and thereby the improvement of QoS. This work proposes an effective bandwidth management approach based on the discrete wavelet transform (DWT). The approach hinges on the results of recent studies showing that while network traffic consists of both long- and short-term dependence, its wavelet coefficients are short-term dependent only. The DWT decomposes the traffic into a low-frequency component and high frequency components. The low- frequency component of the traffic, are significant for long-term traffic behavior and, hence, for bandwidth allocation. The high-frequency components are significant in the short-term behavior of the traffic and, hence, for buffer-allocation.
Claude Turner is an Assistant Professor with the Dept. of Computer Science at Bowie State University in Maryland. He earned his Doctoral degree in Electrical Engineering from the Graduate Center of the City University of New York. His research interests include Bandwidth Management, Network Engineering, and Computer Security.
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In recent years, growing processing power and bandwidth have stimulated a new breed of network applications requiring the development of more sophisticated traffic management algorithms to meet their stringent QoS needs. One of the main obstacles to improving QoS is congestion at network nodes. It is believe that bandwidth prediction is a key component to reducing congestion and thereby the improvement of QoS. This work proposes an effective bandwidth management approach based on the discrete wavelet transform (DWT). The approach hinges on the results of recent studies showing that while network traffic consists of both long- and short-term dependence, its wavelet coefficients are short-term dependent only. The DWT decomposes the traffic into a low-frequency component and high frequency components. The low- frequency component of the traffic, are significant for long-term traffic behavior and, hence, for bandwidth allocation. The high-frequency components are significant in the short-term behavior of the traffic and, hence, for buffer-allocation. 116 pp. Englisch. Nº de ref. del artículo: 9783838314907
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. In recent years, growing processing power and bandwidth have stimulated a new breed of network applications requiring the development of more sophisticated traffic management algorithms to meet their stringent QoS needs. One of the main obstacles to improvi. Nº de ref. del artículo: 5412177
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Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In recent years, growing processing power and bandwidth have stimulated a new breed of network applications requiring the development of more sophisticated traffic management algorithms to meet their stringent QoS needs. One of the main obstacles to improving QoS is congestion at network nodes. It is believe that bandwidth prediction is a key component to reducing congestion and thereby the improvement of QoS. This work proposes an effective bandwidth management approach based on the discrete wavelet transform (DWT). The approach hinges on the results of recent studies showing that while network traffic consists of both long- and short-term dependence, its wavelet coefficients are short-term dependent only. The DWT decomposes the traffic into a low-frequency component and high frequency components. The low- frequency component of the traffic, are significant for long-term traffic behavior and, hence, for bandwidth allocation. The high-frequency components are significant in the short-term behavior of the traffic and, hence, for buffer-allocation. Nº de ref. del artículo: 9783838314907
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Taschenbuch. Condición: Neu. Neuware -In recent years, growing processing power and bandwidth have stimulated a new breed of network applications requiring the development of more sophisticated traffic management algorithms to meet their stringent QoS needs. One of the main obstacles to improving QoS is congestion at network nodes. It is believe that bandwidth prediction is a key component to reducing congestion and thereby the improvement of QoS. This work proposes an effective bandwidth management approach based on the discrete wavelet transform (DWT). The approach hinges on the results of recent studies showing that while network traffic consists of both long- and short-term dependence, its wavelet coefficients are short-term dependent only. The DWT decomposes the traffic into a low-frequency component and high frequency components. The low- frequency component of the traffic, are significant for long-term traffic behavior and, hence, for bandwidth allocation. The high-frequency components are significant in the short-term behavior of the traffic and, hence, for buffer-allocation.Books on Demand GmbH, Überseering 33, 22297 Hamburg 116 pp. Englisch. Nº de ref. del artículo: 9783838314907
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