[hpc-announce] Call for Book Chapters: Big Data Management, Architecture, and Processing

Kuan-Ching Li kuancli at pu.edu.tw
Mon Nov 23 07:05:05 CST 2015


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Call for Book Chapters
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Big Data Management, Architecture, and Processing
(Chapman & Hall/ CRC Big Data Series)
CRC Press, Taylor & Francis Group, USA
https://sites.google.com/site/bigdata2map/

Important Dates
*Proposal Submission: January 15, 2016*
-Proposal Acceptance: February 1, 2016
-Sample Chapter (phase I): May 1, 2016
-Sample Chapter (phase II): July 1, 2016
-Complete Chapter Submission (to editors):   August 1, 2016
-Submission of Chapters (to publisher): August 25, 2016
-Publication Time: Q4/2016 (tentative)


Data are being generated at exponential rate all over the world, and
organizations are storing and processing exponentially increasing
amounts of data. Recently, they have to re-think about and figure out
how to do this efficiently and effectively. Through evolving
algorithms and analytics techniques, organizations can harness data,
discover hidden patterns, and use the derived knowledge to act
meaningfully for competitive advantages.

Book co-editors intend to invite experts and successful case
participating members to contribute discussions on topics for data
gathering and management as well as processing.

This book intends to bridge the gap between huge amount of data and
appropriate computational/management methods for scientific discovery,
and to bring together technologies for media/data communication,
elastic media/data storage, and cross-network media/data fusion. The
book also aims at interesting applications involving Big Data.


Topics
Topics include, but are not limited to, the follows:

* Management
- Big Data Design, implementation, evaluation and services, including
the development process, use cases, experiments and associated
simulations
- Big Data as integration of technologies such as SOA, data mining,
machine learning, HPC, cloud storage, multi-clouds and internet of
things.
- Big Data analytics and visualization with new algorithms showing how
to achieve significant improvements from existing methods
- Query processing and indexing
- Data management within and across multiple geographically
distributed data centers
- Elasticity for data management systems
- Self-*, adaptive and energy-efficient mechanisms
- Performance evaluation of environments and technologies
- Security, privacy, trust, data ownership and risk simulations

*Architecture
- GPU/Many-core and Heterogeneous Architecture
- Energy Efficient Architecture
- Node and System Architecture
- Packaging, Power and Cooling
- Interconnect/Memory Architecture
- Single System Image Clusters
- Big Data Open Systems
- Administration and Maintenance Tools

* Processing
- Techniques, algorithms and innovative methods of processing,
- Business and economic models (quantitative or computational), social
network analyses, scientific workflows and business processes,
- Adoption cases, frameworks and user evaluations involved with
quantitative or computational research methods,
- Data-intensive and scalable computing on hybrid infrastructures,
- MapReduce based computations,
- Many-Task Computing in the Cloud,
- Streaming and real-time processing,
- Big Data applications, experiences and solutions for specific
domains of data science, including security, health, transportation,
logistics, e-government, environment, computational physics,
astronomy, and others.


Proposal submission
A proposal for a book chapter is needed from prospective authors
before the proposal submission due date, describing the goals and
scopes of the proposed chapter. Acceptance of chapter proposals will
be communicated to lead authors after a formal double-blind review
process. The submission of chapter proposals should be sent directly
via email to corresponding editors.


Book Editors
Kuan-Ching Li, Providence University, Taiwan
Hai Jiang, Arkansas State University, USA
Albert Zomaya, The University of Sydney, Australia


Additional Information
Inquiries and chapter proposal submissions can be forwarded
electronically by email to kuancli at pu.edu.tw, hjiang at astate.edu or
albert.zomaya at sydney.edu.au .
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