Call for papers:
The 3rd *IEEE International Conference *on Big Data Science and
Engineering(BDSE2014), 24-26 September 2014, Tsinghua University, Beijing,
China.
Website: http://www.swinflow.org/confs/
Important dates:
Submission Deadline: 11:59PM (UTC/GMT+8 hours) May 5, 2014
Authors Notification: June 30, 2014
Final Manuscript Due: July 20, 2014
Submissions:
http://www.swinflow.org/confs/
Publications
All accepted papers will appear in the proceedings published by IEEE
Computer Society (EI indexed). Selected papers will be recommended to
special issues of Concurrency and Computation: Practice and Experience;
Journal of Network and Computer Applications; Journal of Computer and
System Sciences, and IEEE Transactions on Cloud Computing.
------------
Introduction
Big data is an emerging paradigm applied to datasets whose size is beyond
the ability of commonly used software tools to capture, manage, and process
the data within a tolerable elapsed time. Such datasets are often from
various sources (Variety) yet unstructured such as social media, sensors,
scientific applications, surveillance, video and image archives, Internet
texts and documents, Internet search indexing, medical records, business
transactions and web logs; and are of large size (Volume) with fast data
in/out (Velocity). More importantly, big data has to be of high value
(Value) and establish trust in it for business decision making (Veracity).
Various technologies are being discussed to support the handling of big
data such as massively parallel processing databases, scalable storage
systems, cloud computing platforms, and MapReduce. Big data is more than
simply a matter of size; it is an opportunity to find insights in new and
emerging types of data and content, to make business more agile, and to
answer questions that were previously considered beyond our reach.
Distributed systems is a classical research discipline investigating
various distributed computing technologies and applications such as cloud
computing and MapReduce. With new paradigms and technologies, distributed
systems research keeps going with new innovative outcomes from both
industry and academia. For example, wide deployment of MapReduce is a
distributed programming paradigm and an associated implementation to
support distributed computing over large datasets on cloud.
BDSE (Big Data Science and Engineering) is created to provide a prime
international forum for both researchers, industry practitioners and
environment experts to exchange the latest fundamental advances in the
state of the art and practice of Big Data and broadly related areas.
BDSE 2014 is the next event in a series of highly successful International
Conferences, previously held as BDSE2013 (Sydney Australia), BigDataMR-12
(Xiangtan, China November 2012), AHPCN-12 (Bradford, UK, June 2012),
AHPCN-11 (Banff, Canada, September 2011), AHPCN-10 (Melbourne, Australia,
September 2010), AHPCN-09 (Seoul, Korea, June 2009), AHPCN-08 (Dalian,
China, September 2008).
Scope and Topics
The objective of the conference is to invite authors to submit original
manuscripts that demonstrate and explore current advances in all aspects of
big data and distributed computing. The symposium solicits novel papers on
a broad range of topics, including but not limited to:
? Big Data theory, applications and challenges
? Recent development in Big Data and MapReduce
? Big Data mining and analytics
? Big Data Infrastructure and Cloud Computing
? Big Data visualization
? Large data stream processing on cloud
? Large incremental datasets on cloud
? Distributed and federated datasets
? NoSQL data stores and DB scalability
? Big Data sharing and privacy preserving
? Security, trust and risk in Big Data
? Big Data placement, scheduling, and optimization
? Extension of the MapReduce programming model
? Distributed file systems for Big Data
? MapReduce for Big Data processing, resource scheduling and SLA
? MapReduce on heterogeneous distributed environments
? Performance characterization, evaluation and optimization
? Simulation and debugging of MapReduce and Big Data systems and tools
? Volume, Velocity, Variety, Value and Veracity of Big Data
? Multiple source data processing and integration with MapReduce
? Storage and computation management of Big Data
? Large-scale scientific workflow in support of Big Data processing
? Algorithms and theory for distributed systems
? Data management and distributed data systems
? Security, privacy, fault tolerance and reliability in distributed systems
? Mobile systems and development for handheld devices such as mobile phones
? Big data applications
Submission Guidelines
Submit your paper(s) in PDF file at the BDSE2014 submission site:
http://www.swinflow.org/confs/
limited up to 8 pages in IEEE CS format. The template files for LATEX or
WORD can be downloaded here. All papers will be peer reviewed by two or
three pc members. Submitting a paper to the symposium means that if the
paper is accepted, at least one author should register to BDSE2014 and
attend the conference to present the paper.
Publications
All accepted papers will appear in the proceedings published by IEEE
Computer Society (EI indexed) through CPS. Selected papers will be
recommended for special issues in Concurrency and Computation: Practice and
Experience; Journal of Network and Computer Applications, Journal of
Computer and System Sciences, and IEEE Transactions on Cloud Computing.
General Chairs
Yunhao Liu, Tsinghua University, China
Nick Cercone, York University, Canada
Benjamin Wah, HKCU, China
Program Chairs
Jianzhong Li, Harbin Institute of Technology, China
Rajiv Ranjan, CSIRO, Australia
Eiko Yoneki, Computer Laboratory, University of Cambridge, UK
Dongshen Li, National University of Defence Technology, China
Workshop Chairs
Khaled Mohammed Khan, Qatar University, Qatar
Wanchun Dou, Nanjing University, China
Simon Fong, University of Macau, China
Steering Committee
Albert Zomaya, The University of Sydney, Australia
Ivan Stojmenovic, University of Ottawa, Canada
Geoffrey Fox, Indiana University, USA
Runhe Huang, Hosei University, Japan
Jinjun Chen, University of Technology Sydney, Australia (Chair)
Schahram Dustdar, Vienna University of Technology, Austria
Jian Pei, Simon Fraser University, Canada
Manish Parashar, Rutgers University, USA
Minyi Guo, Shanghai Jiaotong University, China
Jie Wu, Temple University, USA
Laurence T. Yang, St Francis Xavier University, Canada (Chair)
The 3rd *IEEE International Conference *on Big Data Science and
Engineering(BDSE2014), 24-26 September 2014, Tsinghua University, Beijing,
China.
Website: http://www.swinflow.org/confs/
Important dates:
Submission Deadline: 11:59PM (UTC/GMT+8 hours) May 5, 2014
Authors Notification: June 30, 2014
Final Manuscript Due: July 20, 2014
Submissions:
http://www.swinflow.org/confs/
Publications
All accepted papers will appear in the proceedings published by IEEE
Computer Society (EI indexed). Selected papers will be recommended to
special issues of Concurrency and Computation: Practice and Experience;
Journal of Network and Computer Applications; Journal of Computer and
System Sciences, and IEEE Transactions on Cloud Computing.
------------
Introduction
Big data is an emerging paradigm applied to datasets whose size is beyond
the ability of commonly used software tools to capture, manage, and process
the data within a tolerable elapsed time. Such datasets are often from
various sources (Variety) yet unstructured such as social media, sensors,
scientific applications, surveillance, video and image archives, Internet
texts and documents, Internet search indexing, medical records, business
transactions and web logs; and are of large size (Volume) with fast data
in/out (Velocity). More importantly, big data has to be of high value
(Value) and establish trust in it for business decision making (Veracity).
Various technologies are being discussed to support the handling of big
data such as massively parallel processing databases, scalable storage
systems, cloud computing platforms, and MapReduce. Big data is more than
simply a matter of size; it is an opportunity to find insights in new and
emerging types of data and content, to make business more agile, and to
answer questions that were previously considered beyond our reach.
Distributed systems is a classical research discipline investigating
various distributed computing technologies and applications such as cloud
computing and MapReduce. With new paradigms and technologies, distributed
systems research keeps going with new innovative outcomes from both
industry and academia. For example, wide deployment of MapReduce is a
distributed programming paradigm and an associated implementation to
support distributed computing over large datasets on cloud.
BDSE (Big Data Science and Engineering) is created to provide a prime
international forum for both researchers, industry practitioners and
environment experts to exchange the latest fundamental advances in the
state of the art and practice of Big Data and broadly related areas.
BDSE 2014 is the next event in a series of highly successful International
Conferences, previously held as BDSE2013 (Sydney Australia), BigDataMR-12
(Xiangtan, China November 2012), AHPCN-12 (Bradford, UK, June 2012),
AHPCN-11 (Banff, Canada, September 2011), AHPCN-10 (Melbourne, Australia,
September 2010), AHPCN-09 (Seoul, Korea, June 2009), AHPCN-08 (Dalian,
China, September 2008).
Scope and Topics
The objective of the conference is to invite authors to submit original
manuscripts that demonstrate and explore current advances in all aspects of
big data and distributed computing. The symposium solicits novel papers on
a broad range of topics, including but not limited to:
? Big Data theory, applications and challenges
? Recent development in Big Data and MapReduce
? Big Data mining and analytics
? Big Data Infrastructure and Cloud Computing
? Big Data visualization
? Large data stream processing on cloud
? Large incremental datasets on cloud
? Distributed and federated datasets
? NoSQL data stores and DB scalability
? Big Data sharing and privacy preserving
? Security, trust and risk in Big Data
? Big Data placement, scheduling, and optimization
? Extension of the MapReduce programming model
? Distributed file systems for Big Data
? MapReduce for Big Data processing, resource scheduling and SLA
? MapReduce on heterogeneous distributed environments
? Performance characterization, evaluation and optimization
? Simulation and debugging of MapReduce and Big Data systems and tools
? Volume, Velocity, Variety, Value and Veracity of Big Data
? Multiple source data processing and integration with MapReduce
? Storage and computation management of Big Data
? Large-scale scientific workflow in support of Big Data processing
? Algorithms and theory for distributed systems
? Data management and distributed data systems
? Security, privacy, fault tolerance and reliability in distributed systems
? Mobile systems and development for handheld devices such as mobile phones
? Big data applications
Submission Guidelines
Submit your paper(s) in PDF file at the BDSE2014 submission site:
http://www.swinflow.org/confs/
limited up to 8 pages in IEEE CS format. The template files for LATEX or
WORD can be downloaded here. All papers will be peer reviewed by two or
three pc members. Submitting a paper to the symposium means that if the
paper is accepted, at least one author should register to BDSE2014 and
attend the conference to present the paper.
Publications
All accepted papers will appear in the proceedings published by IEEE
Computer Society (EI indexed) through CPS. Selected papers will be
recommended for special issues in Concurrency and Computation: Practice and
Experience; Journal of Network and Computer Applications, Journal of
Computer and System Sciences, and IEEE Transactions on Cloud Computing.
General Chairs
Yunhao Liu, Tsinghua University, China
Nick Cercone, York University, Canada
Benjamin Wah, HKCU, China
Program Chairs
Jianzhong Li, Harbin Institute of Technology, China
Rajiv Ranjan, CSIRO, Australia
Eiko Yoneki, Computer Laboratory, University of Cambridge, UK
Dongshen Li, National University of Defence Technology, China
Workshop Chairs
Khaled Mohammed Khan, Qatar University, Qatar
Wanchun Dou, Nanjing University, China
Simon Fong, University of Macau, China
Steering Committee
Albert Zomaya, The University of Sydney, Australia
Ivan Stojmenovic, University of Ottawa, Canada
Geoffrey Fox, Indiana University, USA
Runhe Huang, Hosei University, Japan
Jinjun Chen, University of Technology Sydney, Australia (Chair)
Schahram Dustdar, Vienna University of Technology, Austria
Jian Pei, Simon Fraser University, Canada
Manish Parashar, Rutgers University, USA
Minyi Guo, Shanghai Jiaotong University, China
Jie Wu, Temple University, USA
Laurence T. Yang, St Francis Xavier University, Canada (Chair)
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