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The emergence of big data and the potential to undertake complex analysis of very large data sets is, essentially, a consequence of recent advances in the technology that allow this. The development of cloud computing over the last few years represents the single most important contributor to the big data trend, with cloud infrastructure such as compute, storage and analytical tools and apps now widely available. The convergence of big data and cloud computing are having far reaching implications that indeed are changing the world. MapReduce, a widely-adopted parallel and distributed programming paradigm for processing large-scale data sets, becomes much more powerful, scalable, elastic and cost-effective when integrated in cloud systems as it can benefits from the salient characteristics of cloud computing. Based on the MapReduce paradigm and other relevant techniques like HDFS, a series of applications and higher level platforms such as Hadoop, Hive, Twister, Spark, Pregel, to name a few, have been proposed and developed. MapReduce and the emerging tools in cloud are ideal for enterprises with large data centres and scientific communities to address the challenges posed by big data applications. The MapReduce paradigm itself, emerging MapReduce based big data tools and applications, and big data infrastructure such as cloud systems are evolving fast, and therefore need extensive investigations from various research communities. This symposium aims at providing a forum for researchers, practitioners and developers from different background areas such as cloud computing, distributed computing, large-scale data management and database areas to exchange the latest experience, research ideas and synergic research and development on fundamental issues and applications about MapReduce, MapReduce based platforms and emerging big data infrastructure. The symposium solicits high quality research results in all related areas. This is the third instalment of the symposium, following the successful events of 2013 (Australia) and 2012 (China). Topics The objective of the symposium is to invite authors to submit original manuscripts that demonstrate and explore current advances in all aspects of MapReduce and big data infrastructure. The symposium solicits novel papers on a broad range of topics, including but not limited to: · Challenges and Opportunities in MapReduce based Big Data Tools and Applications · Recent Development in MapReduce and Big Data Infrastructure · Developing, Debugging and Testing Issues of MapReduce based Big Data Tools · Performance Tuning and Optimization for MapReduce and Big Data Infrastructure · Benchmarking, Evaluation, Simulation for MapReduce based Big Data Tools · Iterative / Recursive MapReduce Systems · Computational Theory for MapReduce based Systems · Extension of the MapReduce Programming Paradigm · Distributed File Systems for MapReduce and Emerging Big Data Tools · Algorithm Analysis and Design with MapReduce Paradigm · Resource Scheduling and SLA of MapReduce for Multiple Users · Heterogeneity and Fault-tolerance in MapReduce based Systems and Big Data Infrastructure · Privacy, Security, Trust and Risk in MapReduce and Big Data Infrastructure · Integration of MapReduce and Emerging Big Data Tools with Cloud / Grid Systems · MapReduce in Hybrid / Fabricated / Federated Cloud Systems · Social Networks Analyses with MapReduce · Data Mining, Analytics, and Visualization using MapReduce · Big Stream / Incremental Data Processing using MapReduce · Big Scientific, Genomic and Healthcare Data Processing with MapReduce · Industrial Experience and Use Cases of MapReduce based Applications · Recent Development Open Source Big Data Infrastructure
Submission Guidelines Submit your paper(s) in PDF file at the MR.BDI2014 submission site: https://www.easychair.org/conferences/?conf=mrbdi2014. 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 BdCloud 2014 and attend the conference to present the paper.
Publication of Papers All accepted papers will appear in the proceedings published by IEEE Computer Society. Distinguished papers will be invited to special issues of BdCloud2014 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.
Important Dates Deadline for Paper Submission: September 5, 2014 (extended, firm) Notification of Acceptance: September 25, 2014 Camera Ready Copies: October 15, 2014 Registration Due: October 15, 2014
General Chairs Timos Sellis, RMIT university, Australia Yanpei Chen, Cloudera, USA Rajkumar Buyya, The University of Melbourne, Australia Jinjun Chen, University of Technology, Sydney, Australia
Program Committee Chairs Nazanin Borhan, University of Technology Sydney, Australia Xuyun Zhang, University of Technology Sydney, Australia Suraj Pandey, IBM Australia Research Lab, Australia
Program Committee Gunter Saake, University of Magdeburg, Germany Jun-Ki Min, Korea university of technology, South Korea Andreas Thor, University of Leipzig, Germany Javid Taheri, University of Sydney, Australia Amund Tveit, Memkite, Norway Soudip Roy Chowdhury, INRIA, Saclay, France Bahman Javadi, University of Western Sydney, Australia Paolo Trunfio, University of Calabria, Italy Chi Yang, University of Technology Sydney, Australia Liana Fong, IBM Research, USA Nikzad Babaii Rizvandi, University of Sydney, Australia Shipin Chen, CSIRO, Australia Roberto Di Pietro, Roma Tre University of Rome, Italy Ray C.C. Cheung, City University of Hong Kong, Hong Kong Hadi Mashinchi, Simavita, Australia Xinyu Que, IBM T.J.Watson Research Center, USA Chao Wang, University of Science and Technology of China, China Hidemoto Nakada, AIST, Japan Boyu Zhang, University of Delaware, USA |