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Record Nr. |
UNINA9910299254103321 |
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Autore |
Wang Dan |
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Titolo |
Sublinear Algorithms for Big Data Applications / / by Dan Wang, Zhu Han |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 |
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ISBN |
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Edizione |
[1st ed. 2015.] |
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Descrizione fisica |
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1 online resource (94 p.) |
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Collana |
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SpringerBriefs in Computer Science, , 2191-5768 |
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Disciplina |
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Soggetti |
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Database management |
Computer networks |
Electrical engineering |
Database Management |
Computer Communication Networks |
Communications Engineering, Networks |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references at the end of each chapters. |
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Nota di contenuto |
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Introduction -- Basics for Sublinear Algorithms -- Applications for Wireless Sensor Networks -- Applications for Big Data Processing -- Applications for a Smart Grid -- Concluding Remarks. |
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Sommario/riassunto |
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The brief focuses on applying sublinear algorithms to manage critical big data challenges. The text offers an essential introduction to sublinear algorithms, explaining why they are vital to large scale data systems. It also demonstrates how to apply sublinear algorithms to three familiar big data applications: wireless sensor networks, big data processing in Map Reduce and smart grids. These applications present common experiences, bridging the theoretical advances of sublinear algorithms and the application domain. Sublinear Algorithms for Big Data Applications is suitable for researchers, engineers and graduate students in the computer science, communications and signal processing communities. |
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