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<div dir="ltr"><div class="gmail_quote"><div dir="ltr"><div class="gmail_quote"><div dir="ltr"><div class="gmail_quote"><div dir="ltr">As requested by dozens of authors, the final deadline for submission is extended to 31 May 2014. But this is firm, no more extension.<div>
<br></div><div><br></div><div>Call for papers:</div>
<div><br>The 3rd <strong>IEEE International Conference </strong>on Big Data Science and Engineering (BDSE2014), 24-26 September 2014, Tsinghua University, Beijing, China.</div>
<div><br>Website: <a href="http://www.swinflow.org/confs/bdse2014/" target="_blank">http://www.swinflow.org/confs/bdse2014/</a></div>
<p><br>Important dates: <br>Submission Deadline: 11:59PM (UTC/GMT+8 hours) May 31, 2014 <b>(firm)</b><br>Authors Notification: June 30, 2014<br>Final Manuscript Due: July 20, 2014</p><p>Submissions:<br><a href="http://www.swinflow.org/confs/bdse2014/submission.htm" target="_blank">http://www.swinflow.org/confs/bdse2014/submission.htm</a></p>
<p><br>Publications<br>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.</p>
<p><br>------------<br>Introduction</p><p>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.</p>
<p>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.</p>
<p>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). <br>
</p><p>Scope and Topics</p><p>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:</p>
<p>· Big Data theory, applications and challenges<br>· Recent development in Big Data and MapReduce<br>· Big Data mining and analytics<br>· Big Data Infrastructure and Cloud Computing<br>· Big Data visualization<br>· Large data stream processing on cloud<br>
· Large incremental datasets on cloud<br>· Distributed and federated datasets<br>· NoSQL data stores and DB scalability<br>· Big Data sharing and privacy preserving<br>· Security, trust and risk in Big Data<br>· Big Data placement, scheduling, and optimization<br>
· Extension of the MapReduce programming model<br>· Distributed file systems for Big Data<br>· MapReduce for Big Data processing, resource scheduling and SLA<br>· MapReduce on heterogeneous distributed environments<br>· Performance characterization, evaluation and optimization<br>
· Simulation and debugging of MapReduce and Big Data systems and tools<br>· Volume, Velocity, Variety, Value and Veracity of Big Data<br>· Multiple source data processing and integration with MapReduce<br>· Storage and computation management of Big Data<br>
· Large-scale scientific workflow in support of Big Data processing<br>· Algorithms and theory for distributed systems<br>· Data management and distributed data systems<br>· Security, privacy, fault tolerance and reliability in distributed systems<br>
· Mobile systems and development for handheld devices such as mobile phones<br>· Big data applications<br> <br>Submission Guidelines</p><p>Submit your paper(s) in PDF file at the BDSE2014 submission site: <a href="http://www.swinflow.org/confs/bdse2014/submission.htm" target="_blank">http://www.swinflow.org/confs/bdse2014/submission.htm</a>. Papers should be 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.</p>
<p> </p><p>Publications<br><br>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.</p>
<div><br>General Chairs<br> Yunhao Liu, Tsinghua University, China<br> Nick Cercone, York University, Canada</div><div> Benjamin Wah, HKCU, China </div><p>Program Chairs<br> Jianzhong Li, Harbin Institute of Technology, China<br>
Rajiv Ranjan, CSIRO, Australia<br> Eiko Yoneki, Computer Laboratory, University of Cambridge, UK<br> Dongshen Li, National University of Defence Technology, China</p><p>Workshop Chairs<br> Khaled Mohammed Khan, Qatar University, Qatar<br>
Wanchun Dou, Nanjing University, China<br> Simon Fong, University of Macau, China<br><br><br>Publication Chairs<br> Jinjun Chen, University of Technology Sydney, Australia<br> Ivan Stojmenovic, University of Ottawa, Canada<br>
</p><p><br>Steering Committee<br> Albert Zomaya,The University of Sydney, Australia<br> Ivan Stojmenovic, University of Ottawa, Canada<br>
Geoffrey Fox, Indiana University, USA<br> Runhe Huang, Hosei University, Japan<br> Ian Foster, Argonne National Laboratory, USA<br> Jinjun Chen, University of Technology Sydney, Australia (Chair)<br> Schahram Dustdar, Vienna University of Technology, Austria<br>
Stephen Crago, University of Southern California, USA<br> Jian Pei, Simon Fraser University, Canada<br> Manish Parashar, Rutgers University, USA<br> Minyi Guo, Shanghai Jiaotong University, China<br> Jie Wu, Temple University, USA<br>
Laurence T. Yang, St Francis Xavier University, Canada (Chair)</p></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div>