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Server scalability can be greatly enhanced with hybrid data dissemination that combines multicast and unicast techniques. Multicast is ideal for popular data. It aggregates multiple unicast data transfers into a single transmission and is thus more scalable than unicast. On the other hand, multicast is inappropriate for unpopular data since it would force unwanted contents on most clients. As a result, hybrid data dissemination would ideally achieve scalable utilization of server and network resources while avoiding the reception of unneeded contents.In this work, we first present a deployment framework for hybrid data delivery in the Internet. Then, we study a fundamental problem in hybrid data dissemination: document selection, which determines the transfer method that is most appropriate for each data item. We individuate special challenges, such as scalable and robust popularity estimation, appropriate classification of documents, and unpopular large documents. In addition, we examine other critical issues including multicast performance evaluation and application level multicast protocols. Our work contributes to building practical hybrid data dissemination network services.
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Informazioni sull'autore
I was born in Hangzhou, Zhejiang Province, China. I lived in this beautiful city for more than 20 years until I left for my doctoral study in USA. I received a PhD degree in Computer Science from Case Western Reserve University, Cleveland, OH, USA, in 2007. I also have BS and MS degrees in Computer Science from Zhejiang University, China.
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Scalable Hybrid Data Dissemination for Inetrnet Hot Spots
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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Server scalability can be greatly enhanced with hybrid data dissemination that combines multicast and unicast techniques. Multicast is ideal for popular data. It aggregates multiple unicast data transfers into a single transmission and is thus more scalable than unicast. On the other hand, multicast is inappropriate for unpopular data since it would force unwanted contents on most clients. As a result, hybrid data dissemination would ideally achieve scalable utilization of server and network resources while avoiding the reception of unneeded contents.In this work, we first present a deployment framework for hybrid data delivery in the Internet. Then, we study a fundamental problem in hybrid data dissemination: document selection, which determines the transfer method that is most appropriate for each data item. We individuate special challenges, such as scalable and robust popularity estimation, appropriate classification of documents, and unpopular large documents. In addition, we examine other critical issues including multicast performance evaluation and application level multicast protocols. Our work contributes to building practical hybrid data dissemination network services. Codice articolo 9783836485883
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Scalable Hybrid Data Dissemination for Inetrnet Hot Spots
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Taschenbuch. Condizione: Neu. Scalable Hybrid Data Dissemination for Inetrnet Hot Spots | Wenhui Zhang | Taschenbuch | Englisch | VDM Verlag Dr. Müller | EAN 9783836485883 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Codice articolo 101825833
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SCALABLE HYBRID DATA DISSEMINATION FOR INTERNET HOT SPOTS
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VDM Verlag Dr. Müller, 2008
ISBN 10: 3836485885
ISBN 13: 9783836485883
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Paperback. Condizione: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book. Codice articolo ERICA79038364858856
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