Multimedia big data computing for IoT applications: concepts, paradigms and solutions / edited by Tanwar, Sudeep, Tyagi, Sudhanshu, and Kumar, Neeraj.

Contributor(s):

Material type: Text

TextSeries: Intelligent systems reference library, 163Publication details: Singapore : Cengage Learning Asia Pte Ltd., 2020.Description: xiv, 477 pages : col. illus. ; 24 cmISBN:

9789811387586

Subject(s):

DDC classification:

Ref 005.71 M91m 2023

Contents:

Part I. Technological developments - - Part II. Multimedia big data analytics - - Part III. Societal impact of multimedia big data - - Part IV. Application environments.

Summary: "This book considers all aspects of managing the complexity of Multimedia Big Data Computing (MMBD) for IoT applications and develops a comprehensive taxonomy. It also discusses a process model that addresses a number of research challenges associated with MMBD, such as scalability, accessibility, reliability, heterogeneity, and Quality of Service (QoS) requirements, presenting case studies to demonstrate its application. Further, the book examines the layered architecture of MMBD computing and compares the life cycle of both big data and MMBD. Written by leading experts, it also includes numerous solved examples, technical descriptions, scenarios, procedures, and algorithms." - - provided by publisher

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Holdings
Item type	Current library	Collection	Call number	Status	Barcode	Course reserves
Books	ASCOT Library - Zabali Campus Reference	Reference	Ref 005.71 M91m 2023 (Browse shelf(Opens below))	Available	Ref0057104524	List of New Acquisitions

Includes bibliographical references.

Part I. Technological developments - -
Part II. Multimedia big data analytics - -
Part III. Societal impact of multimedia big data - -
Part IV. Application environments.

"This book considers all aspects of managing the complexity of Multimedia Big Data Computing (MMBD) for IoT applications and develops a comprehensive taxonomy. It also discusses a process model that addresses a number of research challenges associated with MMBD, such as scalability, accessibility, reliability, heterogeneity, and Quality of Service (QoS) requirements, presenting case studies to demonstrate its application. Further, the book examines the layered architecture of MMBD computing and compares the life cycle of both big data and MMBD. Written by leading experts, it also includes numerous solved examples, technical descriptions, scenarios, procedures, and algorithms." - - provided by publisher

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