<div class="gmail_quote"><div>Call for papers:<br><br>The 2nd IEEE International Conference on Big Data and Distributed Systems (BDDS2013), 3-5 December 2013, Sydney, Australia - <br><a href="http://www.swinflow.org/confs/bdds2013/" target="_blank">http://www.swinflow.org/confs/bdds2013/</a><br>
<br><br>Important dates: <br>Workshop Proposal: May 30, 2013<br>Submission Deadline: July 15, 2013<br>Authors Notification: September 15, 2013<br>Final Manuscript Due: September 30, 2013<br>Registration Due: September 30, 2013<br>
Conference dates: December 3-5, 2013<br><br>Submission site:<br><a href="https://www.easychair.org/conferences/?conf=bdds2013" target="_blank">https://www.easychair.org/conferences/?conf=bdds2013</a><br><br><br>------------<br>
Introduction<br>
<br>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). 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. 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. Following its success in 2012 as BigDataMR2012 workshop, this conference aims at providing a forum for researchers, practitioners and developers from different background areas such as data intensive computing, computational science, cloud computing, distributed computing and database <br>
area to exchange the latest experience, research ideas and synergic research and development on fundamental issues and applications about big data and distributed systems. The symposium solicits high quality research results in all related areas.<br>
<br>BDDS (Big Data and Distributed Systems) 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, Distributed Systems and broadly related areas.<br>
<br> <br>Scope and Topics<br><br>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:<br>
<br>· Big Data theory, applications and challenges<br>· Recent development in Big Data and MapReduce<br>· Big Data mining and analytics<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 and Value of Big Data (4V)<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>
· Distributed ad hoc, ubiquitous and pervasive systems<br>· Mobile systems and development for handheld devices such as mobile phones<br>· Distributed system architectures and software such as runtime systems, multicore programming languages, performance modelling and evaluation, programming environments and tools, and etc.<br>
· Distributed computing applications such as management of big data, scientific applications, social media applications, web applications and mobile computing<br><br> <br>Submission Guidelines<br>Submit your paper(s) in PDF file at the BDDS2012 submission site: <a href="https://www.easychair.org/conferences/?conf=bdds2013" target="_blank">https://www.easychair.org/conferences/?conf=bdds2013</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 BDDS2013 and attend the conference to present the paper.<br>
<br> <br>Publications<br>All accepted papers will appear in the proceedings published by IEEE Computer Society (EI indexed, pending). Selected papers will be invited to special issues of high quality international journals (TBA).<br>
<br><br>Honorary Chairs<br> Ramamohanarao Kotagiri, The University of Melbourne, Australia<br> Albert Zomaya, The University of Sydney, Australia<br><br>General Chairs<br> Jian Pei, Simon Fraser University, Canada<br>
Xian-He Sun, Illinois Institute of Technology, USA<br> Xuemin Lin, University of New South Wales, Australia<br><br>General Vice Chairs<br> Jiannong Cao, Poly. University Hong Kong, China<br> Zahir Tari, RMIT University, Australia<br>
Rajkumar Buyya, The University of Melbourne, Australia<br><br>Program Chairs<br> Jinjun Chen, University of Technology, Sydney, Australia<br> Surya Nepal, CSIRO, Australia<br> Massimo Cafaro, University of Salento, Lecce, Italy<br>
<br>Workshop Chairs<br> Rajiv Rajan, CSIRO, Australia<br> Xuyun Zhang, University of Technology Sydney, Australia<br><br>Steering Committee Co-Chairs<br> Jinjun Chen, University of Technology Sydney, Australia<br>
Laurence T. Yang, St Francis Xavier University, Canada
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