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This handbook is carefully edited book – contributors are worldwide experts in
the field of data intensive computing and their applications. The scope of the
book includes leading edge data intensive computing architectures and systems,
innovative storage, virtualization, and parallel processing technologies applied in
data intensive computing, and a variety of data intensive applications.
Data intensive computing refers to capturing, managing, analyzing, and understanding
data at volumes and rates that push the frontiers of current technologies.
The challenge of data intensive computing is to provide the hardware architectures
and related software systems and techniques which are capable of transforming
ultra-large data into valuable knowledge. Data intensive computing demands a fundamentally
different set of principles than mainstream computing. Data-intensive
applications typically are well suited for large-scale parallelism over the data and
also require extremely high degree of fault-tolerance, reliability, and availability.
In addition, most data intensive applications require real-time or near real-time
response. The objective of the project is to introduce the basic concepts of data
intensive computing, technologies and hardware and software techniques applied in
data intensive computing, and current and future applications.
The handbook comprises of four parts, which consist of 30 chapters. The first part
on Architectures and Systems includes chapters dealing with network architectures
for data intensive computing, data intensive software systems, and high-level
programming languages and storage systems for data-intensive computing. The
second part on Technologies and Techniques covers load balancing techniques,
linking technologies, virtualization techniques, feature ranking methods and other
techniques applied in data intensive computing. The third part on Security includes
various aspects on privacy and security requirements and related techniques applied
in data intensive computing. The fourth part on Applications describes various data
intensive applications from earthquake simulations and geosciences to biological
systems, social information systems, and bioinformatics. |