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With the number of machine-to-machine (M2M)-enabled devices
projected to reach 20 to 50 billion by 2020, there is a critical
need to understand the demands imposed by such systems.
Machine-to-Machine Communications: Architectures, Technology,
Standards, and Applications offers rigorous treatment of the many
facets of M2M communication, including its integration with current
technology. Presenting the work of a different group of
international experts in each chapter, the book begins by supplying
an overview of M2M technology. It considers proposed standards,
cutting-edge applications, architectures, and traffic modeling and
includes case studies that highlight the differences between
traditional and M2M communications technology. Details a practical
scheme for the forward error correction code design Investigates
the effectiveness of the IEEE 802.15.4 low data rate wireless
personal area network standard for use in M2M communications
Identifies algorithms that will ensure functionality, performance,
reliability, and security of M2M systems Illustrates the
relationship between M2M systems and the smart power grid Presents
techniques to ensure integration with and adaptation of existing
communication systems to carry M2M traffic Providing authoritative
insights into the technologies that enable M2M communications, the
book discusses the challenges posed by the use of M2M
communications in the smart grid from the aspect of security and
proposes an efficient intrusion detection system to deal with a
number of possible attacks. After reading this book, you will
develop the understanding required to solve problems related to the
design, deployment, and operation of M2M communications networks
and systems.
With the number of machine-to-machine (M2M)-enabled devices
projected to reach 20 to 50 billion by 2020, there is a critical
need to understand the demands imposed by such systems.
Machine-to-Machine Communications: Architectures, Technology,
Standards, and Applications offers rigorous treatment of the many
facets of M2M communication, including its integration with current
technology. Presenting the work of a different group of
international experts in each chapter, the book begins by supplying
an overview of M2M technology. It considers proposed standards,
cutting-edge applications, architectures, and traffic modeling and
includes case studies that highlight the differences between
traditional and M2M communications technology. Details a practical
scheme for the forward error correction code design Investigates
the effectiveness of the IEEE 802.15.4 low data rate wireless
personal area network standard for use in M2M communications
Identifies algorithms that will ensure functionality, performance,
reliability, and security of M2M systems Illustrates the
relationship between M2M systems and the smart power grid Presents
techniques to ensure integration with and adaptation of existing
communication systems to carry M2M traffic Providing authoritative
insights into the technologies that enable M2M communications, the
book discusses the challenges posed by the use of M2M
communications in the smart grid from the aspect of security and
proposes an efficient intrusion detection system to deal with a
number of possible attacks. After reading this book, you will
develop the understanding required to solve problems related to the
design, deployment, and operation of M2M communications networks
and systems.
Networking for Big Data supplies an unprecedented look at
cutting-edge research on the networking and communication aspects
of Big Data. Starting with a comprehensive introduction to Big Data
and its networking issues, it offers deep technical coverage of
both theory and applications. The book is divided into four
sections: introduction to Big Data, networking theory and design
for Big Data, networking security for Big Data, and platforms and
systems for Big Data applications. Focusing on key networking
issues in Big Data, the book explains network design and
implementation for Big Data. It examines how network topology
impacts data collection and explores Big Data storage and resource
management. Addresses the virtual machine placement problem
Describes widespread network and information security technologies
for Big Data Explores network configuration and flow scheduling for
Big Data applications Presents a systematic set of techniques that
optimize throughput and improve bandwidth for efficient Big Data
transfer on the Internet Tackles the trade-off problem between
energy efficiency and service resiliency The book covers
distributed Big Data storage and retrieval as well as security,
trust, and privacy protection for Big Data collection, storage, and
search. It discusses the use of cloud infrastructures and
highlights its benefits to overcome the identified issues and to
provide new approaches for managing huge volumes of heterogeneous
data. The text concludes by proposing an innovative user data
profile-aware policy-based network management framework that can
help you exploit and differentiate user data profiles to achieve
better power efficiency and optimized resource management.
Networking for Big Data supplies an unprecedented look at
cutting-edge research on the networking and communication aspects
of Big Data. Starting with a comprehensive introduction to Big Data
and its networking issues, it offers deep technical coverage of
both theory and applications. The book is divided into four
sections: introduction to Big Data, networking theory and design
for Big Data, networking security for Big Data, and platforms and
systems for Big Data applications. Focusing on key networking
issues in Big Data, the book explains network design and
implementation for Big Data. It examines how network topology
impacts data collection and explores Big Data storage and resource
management. Addresses the virtual machine placement problem
Describes widespread network and information security technologies
for Big Data Explores network configuration and flow scheduling for
Big Data applications Presents a systematic set of techniques that
optimize throughput and improve bandwidth for efficient Big Data
transfer on the Internet Tackles the trade-off problem between
energy efficiency and service resiliency The book covers
distributed Big Data storage and retrieval as well as security,
trust, and privacy protection for Big Data collection, storage, and
search. It discusses the use of cloud infrastructures and
highlights its benefits to overcome the identified issues and to
provide new approaches for managing huge volumes of heterogeneous
data. The text concludes by proposing an innovative user data
profile-aware policy-based network management framework that can
help you exploit and differentiate user data profiles to achieve
better power efficiency and optimized resource management.
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Nadine Gordimer
Paperback
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R398
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Discovery Miles 3 300
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