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Sublinear Algorithms for Big Data Applications / by Dan Wang, Zhu Han.

By: Contributor(s): Material type: TextTextLanguage: İngilizce Series: SpringerBriefs in Computer SciencePublisher: Cham : Springer International Publishing : Imprint: Springer, 2015Description: 1 online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783319204482
Subject(s): LOC classification:
  • QA76.9.D3
Online resources:
Contents:
Introduction -- Basics for Sublinear Algorithms -- Applications for Wireless Sensor Networks -- Applications for Big Data Processing -- Applications for a Smart Grid -- Concluding Remarks.
Summary: 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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Holdings
Item type Current library Home library Collection Call number Status Notes Date due Barcode
E-Book E-Book Merkez Kütüphane Merkez Kütüphane E-Kitap Koleksiyonu QA76.9.D3EBK (Browse shelf(Opens below)) Geçerli değil-e-Kitap / Not applicable-e-Book EBK00908

Introduction -- Basics for Sublinear Algorithms -- Applications for Wireless Sensor Networks -- Applications for Big Data Processing -- Applications for a Smart Grid -- Concluding Remarks.

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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Devinim Yazılım Eğitim Danışmanlık tarafından Koha'nın orjinal sürümü uyarlanarak geliştirilip kurulmuştur.