Video Processing Cloud by Pereira Rafael (16 results)
Language: English
Published by Springer, 2011
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Published by Springer, 2011
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Language: English
Published by Springer, 2011
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Published by Springer, 2011
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Language: English
Published by Springer, 2011
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Published by Springer 2011-08, 2011
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Language: English
Published by Springer, 2011
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Language: English
Published by Springer, 2011
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Published by Springer-Verlag New York Inc, 2011
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Language: English
Published by Springer, Springer, 2011
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - As computer systems evolve, the volume of data to be processed increases significantly, either as a consequence of the expanding amount of available information, or due to the possibility of performing highly complex operations that were not feasib…le in the past. Nevertheless, tasks that depend on the manipulation of large amounts of information are still performed at large computational cost, i.e., either the processing time will be large, or they will require intensive use of computer resources. In this scenario, the efficient use of available computational resources is paramount, and creates a demand for systems that can optimize the use of resources in relation to the amount of data to be processed. This problem becomes increasingly critical when the volume of information to be processed is variable, i.e., there is a seasonal variation of demand. Such demand variations are caused by a variety of factors, such as an unanticipated burst of client requests, a time-critical simulation,or high volumes of simultaneous video uploads, e.g. as a consequence of a public contest. In these cases, there are moments when the demand is very low (resources are almost idle) while, conversely, at other moments, the processing demand exceeds the resources capacity. Moreover, from an economical perspective, seasonal demands do not justify a massive investment in infrastructure, just to provide enough computing power for peak situations. In this light, the ability to build adaptive systems, capable of using on demand resources provided by Cloud Computing infrastructures is very attractive.
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Published by Springer, 2011
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Taschenbuch. Condition: Neu. Video Processing in the Cloud | Rafael Silva Pereira (u. a.) | Taschenbuch | SpringerBriefs in Computer Science | v | Englisch | 2011 | Springer | EAN 9781447121367 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com… | Anbieter: preigu.
Language: English
Published by Springer London, 2011
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Condition: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | As computer systems evolve, the volume of data to be processed increases significantly, either as a consequence of the expanding amount of available information, or due to the possibility of performing highly complex operations that were not feasib…le in the past. Nevertheless, tasks that depend on the manipulation of large amounts of information are still performed at large computational cost, i.e., either the processing time will be large, or they will require intensive use of computer resources. In this scenario, the efficient use of available computational resources is paramount, and creates a demand for systems that can optimize the use of resources in relation to the amount of data to be processed. This problem becomes increasingly critical when the volume of information to be processed is variable, i.e., there is a seasonal variation of demand. Such demand variations are caused by a variety of factors, such as an unanticipated burst of client requests, a time-critical simulation,or high volumes of simultaneous video uploads, e.g. as a consequence of a public contest. In these cases, there are moments when the demand is very low (resources are almost idle) while, conversely, at other moments, the processing demand exceeds the resources capacity. Moreover, from an economical perspective, seasonal demands do not justify a massive investment in infrastructure, just to provide enough computing power for peak situations. In this light, the ability to build adaptive systems, capable of using on demand resources provided by Cloud Computing infrastructures is very attractive.
Language: English
Published by Springer, 2011
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Condition: New. Print on Demand pp. 74 19 Illus.
Language: English
Published by Springer, 2011
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Condition: New. PRINT ON DEMAND pp. 74.
Language: English
Published by Springer London, 2011
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Propose a general architecture for large scale distributed video processing systemDevelop an algorithm that allows parallel and distributed task processingIdentifies and provides a precise formulation of problems char…acterized by the season.
Language: English
Published by Springer, Springer Aug 2011, 2011
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -As computer systems evolve, the volume of data to be processed increases significantly, either as a consequence of the expanding amount of available information, or due to the possibility of performing highly complex operations that wer…e not feasible in the past. Nevertheless, tasks that depend on the manipulation of large amounts of information are still performed at large computational cost, i.e., either the processing time will be large, or they will require intensive use of computer resources. In this scenario, the efficient use of available computational resources is paramount, and creates a demand for systems that can optimize the use of resources in relation to the amount of data to be processed. This problem becomes increasingly critical when the volume of information to be processed is variable, i.e., there is a seasonal variation of demand. Such demand variations are caused by a variety of factors, such as an unanticipated burst of client requests, a time-critical simulation,or high volumes of simultaneous video uploads, e.g. as a consequence of a public contest. In these cases, there are moments when the demand is very low (resources are almost idle) while, conversely, at other moments, the processing demand exceeds the resources capacity. Moreover, from an economical perspective, seasonal demands do not justify a massive investment in infrastructure, just to provide enough computing power for peak situations. In this light, the ability to build adaptive systems, capable of using on demand resources provided by Cloud Computing infrastructures is very attractive.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 72 pp. Englisch.
