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Books > Computing & IT > General theory of computing
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Data Science and Big Data Analytics in Smart Environments (Hardcover)
Loot Price: R4,317
Discovery Miles 43 170
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Data Science and Big Data Analytics in Smart Environments (Hardcover)
Expected to ship within 12 - 17 working days
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Most applications generate large datasets, like social networking
and social influence programs, smart cities applications, smart
house environments, Cloud applications, public web sites,
scientific experiments and simulations, data warehouse, monitoring
platforms, and e-government services. Data grows rapidly, since
applications produce continuously increasing volumes of both
unstructured and structured data. Large-scale interconnected
systems aim to aggregate and efficiently exploit the power of
widely distributed resources. In this context, major solutions for
scalability, mobility, reliability, fault tolerance and security
are required to achieve high performance and to create a smart
environment. The impact on data processing, transfer and storage is
the need to re-evaluate the approaches and solutions to better
answer the user needs. A variety of solutions for specific
applications and platforms exist so a thorough and systematic
analysis of existing solutions for data science, data analytics,
methods and algorithms used in Big Data processing and storage
environments is significant in designing and implementing a smart
environment. Fundamental issues pertaining to smart environments
(smart cities, ambient assisted leaving, smart houses, green
houses, cyber physical systems, etc.) are reviewed. Most of the
current efforts still do not adequately address the heterogeneity
of different distributed systems, the interoperability between
them, and the systems resilience. This book will primarily
encompass practical approaches that promote research in all aspects
of data processing, data analytics, data processing in different
type of systems: Cluster Computing, Grid Computing, Peer-to-Peer,
Cloud/Edge/Fog Computing, all involving elements of heterogeneity,
having a large variety of tools and software to manage them. The
main role of resource management techniques in this domain is to
create the suitable frameworks for development of applications and
deployment in smart environments, with respect to high performance.
The book focuses on topics covering algorithms, architectures,
management models, high performance computing techniques and
large-scale distributed systems.
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