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Big Data Related Technologies, Challenges and Future Prospects

Identifier --minchenshi-1151
Penulis / PengarangMin Chen Ӣ Shiwen Mao Ӣ Yin Zhang Victor C.M. Leung
Kata Kunci Challenges and Future Prospects
Tanggal Publikasi09 Mar 2014
BahasaBahasa Inggris
Abstrak / Deskripsi “Howbigisbig?”SciencewriterStephenStraussasksinhisfunbookforkidstitled How Big is Big and explains that “bigness is somethingno one can consume.” In this book, we aim to answer this interesting question, but in the context of computer data. In the big data era, we are dealing with the explosive increase of global data and enormous datasets. Unlike seemingly similar terms such as “massive data” or “very big data,” big data refers to the datasets that could not be perceived,acquired,managed,andprocessedbytraditionalInformationTechnology (IT) and software/hardwaretools within a tolerable time. It can be characterized by four Vs, i.e., Volume (great volume), Variety (various modalities), Velocity (rapid generation),and Value (huge value but very low density). Inthisbook,weprovideacomprehensiveoverviewofthebackgroundandrelated technologies, challenges and future prospects of big data. We first introduce the general background of big data and review related technologies, such as cloud computing, Internet of Things (IoT), data centers, and Hadoop. We then focus on the four phases of the value chain of big data, i.e., data generation, data acquisition,datastorage,anddataanalysis.Foreachphase,weintroducethegeneral background, discuss the technical challenges, and review the latest advances. We nextexaminetheseveralrepresentativeapplicationsofbigdata,includingenterprise management, IoT, online social networks, healthcare and medical applications, collective intelligence, and smart grid. This book is concluded with a discussion of openproblemsandfuturedirections.Weaimtoprovidethereadersacomprehensive overview and big-picture of this exciting area. We hope this monograph could be a usefulreferenceforgraduatestudentsandprofessionalsinrelatedfields,andgeneral readers who will benefit from an understandingof the big data field.

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