May 2014 - ogsa-wg - lists.ogf.org

CFP: IEEE BDSE2014 (Big Data Science and Engineering), Tsinghua University, Beijing, China, Sept. 2014
by Chang Liu 18 May '14

18 May '14

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/bdse2014/ Important dates: Submission Deadline: 11:59PM (UTC/GMT+8 hours) May 31, 2014 *(extended, firm)* Authors Notification: June 30, 2014 Final Manuscript Due: July 20, 2014 Submissions: http://www.swinflow.org/confs/bdse2014/submission.htm 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/bdse2014/submission.htm. 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. 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 Publication Chairs Jinjun Chen, University of Technology Sydney, Australia Ivan Stojmenovic, University of Ottawa, Canada 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 Ian Foster, Argonne National Laboratory, USA Jinjun Chen, University of Technology Sydney, Australia (Chair) Schahram Dustdar, Vienna University of Technology, Austria Stephen Crago, University of Southern California, USA 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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CFP: PriSec 2014 (The 3rd International Symposium on Privacy and Security in Cloud and Big Data), 3-5 December 2014, Sydney, Australia.
by DEEPAK PUTHAL 10 May '14

10 May '14

Call for papers: The 3rd International Symposium on Privacy and Security in Cloud and Big Data (PriSec 2014), 3-5 December 2014, Sydney, Australia Website: http://www.swinflow.org/confs/prisec2014/ Important dates: Deadline for Paper Submission: June 25, 2014 Notification of Acceptance: August 25, 2014 Camera Ready Copies: October 15, 2014 Submissions: https://www.easychair.org/conferences/?conf=prisec2014 Publications: All accepted papers will appear in the proceedings published by IEEE Computer Society (EI indexed). Selected papers will be invited to special issues of BdCloud 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. ------------ Introduction: Cloud Computing and Big Data are two emerging paradigms in the recent developments of information technology. Cloud Computing enables computing resources to be provided as IT services in a pay-as-you-go fashion with high efficiency and effectiveness. 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.With Variety/Volume/Velocity/Value/Veracity/, Big Data such as medical records need to be protected in an scalable and efficient way. Information privacy and security is one of most concerned issues for Cloud Computing due to its open environment with very limited user-side control. It is also an important challenge for Big Data as estimated by IDC. In addition, Cloud Computing and Big Data are coming together in practice. As estimated by IDC, by 2020, about 40% data globally would be touched with Cloud Computing. Cloud Computing provides strong storage, computation and distributed capability in support of Big Data processing. As such, there is a strong demand to investigate information privacy and security challenges in both Cloud Computing and Big Data. This symposium aims at providing such forum for researchers, practitioners and developers from different background areas such as distributed computing, cloud computing, big data, database, data mining, information security and privacy protection areas to exchange the latest experience, research ideas and synergic research and development on fundamental issues and applications about security and privacy issues in cloud and big data environments. 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 (Karlsruhe, Germany) and 2012 (Xiangtan, China). Scope and Topics: The objective of this symposium is to invite authors to submit original manuscripts that demonstrate and explore current advances in all aspects of security and privacy in cloud computing environments. The symposium solicits novel papers on a broad range of topics, including but not limited to: Track 1: Privacy and Security in Cloud · Privacy modelling in cloud computing · Privacy correlation between multiple services in cloud computing · Trust based privacy protection in cloud computing · Privacy categorisation in cloud computing · Privacy models for outsourcing · Privacy preserving data publishing on cloud · User privacy, service providers privacy and cloud platform privacy · Privacy requirements engineering on cloud · Private information retrieval on cloud · Privacy and security in personal health records on cloud · Privacy mechanisms in cloud services · Privacy aware scheduling in cloud · Security models, levels and scenarios in cloud computing · Secure identity management in clouds · Secure data management in cloud computing · Secure access to clouds · Remote data integrity protection · Securing distributed data storage in the cloud · Data-centric security and data classification · Cost and usability models related security issues in clouds · Interaction security between usability models in cloud computing · Secure Job deployment and scheduling on cloud · Secure resource allocation and indexing · User authentication and authorisation in cloud services · Auditing in cloud computing · Cloud threat models · Multi-tenancy related security/privacy issues · Security/privacy/trust issues in SaaS/PaaS/IaaS · Secure virtual machine mechanisms in cloud computing · Vulnerabilities in cloud infrastructure · Vulnerabilities in MapReduce · Fault tolerance, exception handling and reliability issues in cloud · Application programming environment Track 2: Privacy and Security in Big Data · Secure quantum communications · Privacy in Big Data applications and services · Privacy in Big Data end-point input validation and filtering · Privacy in Big Data integration and transformation · Privacy in parallel and distributed computation · Privacy in Big Data storage management · Privacy in Big Data access control mechanisms · Privacy in Big Data mining and analytics · Privacy in Big Data sharing and visualization · Big Data privacy policies and standards · Security model and architecture for Big Data · Data mining security for Big Data · Software and system security for Big Data · Cryptography in Big Data · Visualizing large scale security data · Threat detection using Big Data analytics · Human computer interaction challenges for Big Data security · Data protection, integrity standards and policies · Security and legislative impacts for Big Data · Managing user access for Big Data · Scalability and auditing for Big Data Submission Guidelines: Submit your papers in PDF file at the PriSec2014 submission site: https://www.easychair.org/conferences/?conf=prisec2014. Papers should be limited up to 8 pages in IEEE format. Templates can be downloaded here for Word <http://kpnm.hnust.cn/confs/cgc2012/IEEECS_CPS_8.5x11x2.zip> or LATEX<http://kpnm.hnust.cn/confs/cgc2012/IEEECS_CPS_LaTeX_Letter_2Col.zip>. All papers will be peer reviewed by two or three PC members. Submitting a paper to the workshop means that if the paper is accepted, at least one author should register to BdCloud<http://www.swinflow.org/confs/bdcloud2014> 2014 <http://www.swinflow.org/confs/bdcloud2014> and attend the conference to present the paper. Publications: All accepted papers will appear in the proceedings published by IEEE Computer Society (EI indexed). Selected papers will be invited to special issues of BdCloud 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: Chita R. Das, Pennsylvania State University, USA Vijay Varadharajan, Macquarie University, Australia Program Committee Chairs: Deepak Puthal, University of Technology, Sydney, Australia Chang Liu, University of Technology, Sydney, Australia Rajiv Ranjan, CSIRO, Australia Jinjun Chen, University of Technology, Sydney, Australia Program Committees: Cristina Alcaraz, University of Malaga, Spain Shlomi Dolev, Ben-Gurion University, Israel Yevgeniy Vahlis, University of Toronto Canada Guenther Pernul, University of Regensburg, Germany Charles Morisset, Newcastle University, UK David Naccache, ENS, France Dieter Gollmann, TU Hamburg-Harburg, Germany Yang Xiang, Deakin University, Australia Bibhudatta Sahoo, NIT Rourkela, India Kartik Gopalan, SUNY - Binghamton, USA Joanna Kolodziej, Cracow University of Technology, Poland Yves-Alexandre de Montjoye, MIT, USA Henrik Johnsson, Blekinge Institute of Technology, Sweden Ching-Hsien Hsu, Chung Hua University, Taiwan Biswapratap Singh Sahoo, National Central University, Taiwan Zeeshan Hameed, QMIC, Qatar Roberto Di Pietr, Bell Labs, France Rino Falcone, ISTC-CNR, Italy Stefano Guarino, Università degli Studi Roma Tr, Italy Abhinav Srivastava, AT&T Labs, USA Siani Pearson, HP Labs, UK Changhoon Lee, Seoul National University of Science and Technology, Korea Nour Ali, University of Brighton, UK Wei Wei, Xi'an University of Technology, China Sherman S. M. Chow, Chinese University of Hong Kong Stefano Paraboschi, Università degli Studi di Bergamo, Italy Ramlan Mahmood, University Putra Malaysia

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CFP: [MR.BDI 2014] The 3rd International Symposium on MapReduce and Big Data Infrastructure, 03-05 December 2014, Sydney, Australia
by Nazanin Borhan 10 May '14

10 May '14

[We apologize if you receive multiple copies of this CFP.] Call for Papers – Deadline July 30, 2014 The 3rd International Symposium on MapReduce and Big Data Infrastructure (MR.BDI 2014) 03-05 December 2014, Sydney, Australia Co-located with the 4th IEEE International Conference on Big Data and Cloud Computing (BdCloud 2014 <http://www.swinflow.org/confs/bdcloud2014/>). Sponsored by Sponsored by IEEE TCSC <http://www.ieeetcsc.org/> Technical Area on Big Data and MapReduce http://www.swinflow.org/confs/mrbdi2014/ -------------------------------------------------------------------------------------------------------------------------------- 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 <http://www.swinflow.org/confs/mrbdi2013/> (Australia) and 2012 <http://www.swinflow.org/confs/bigdatamr2012> (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<http://kpnm.hnust.cn/confs/cgc2012/IEEECS_CPS_LaTeX_Letter_2Col.zip> or WORD <http://kpnm.hnust.cn/confs/cgc2012/IEEECS_CPS_8.5x11x2.zip>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<http://www.swinflow.org/confs/bdcloud2014/> and attend the conference to present the paper. ------------------------------------------------------------------------------------------------------------------------------ Publication of paper: All accepted papers will appear in the proceedings published by IEEE Computer Society (EI indexed). 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: July 30, 2014 Notification of Acceptance: September 25, 2014 Camera Ready Copies: October 15, 2014 Registration Due: October 15, 2014 ------------------------------------------------------------------------------------------------------------------------------ General Chairs: Yanpei Chen, Cloudera, USA Rajkumar Buyya, 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 Committees: Gunter Saake, University of Magdeburg, Germany 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 Jun-Ki Min, Korea university of technology, South Korea Ray C.C. Cheung, City University of Hong Kong, Hong Kong Hadi Mashinchi, Simavita, Australia Chao Wang, University of Science and Technology of China, China Hidemoto Nakada, AIST, Japan Boyu Zhang, University of Delaware, USA

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CFP - IEEE TCC Special Issue on "Big Data Computing on Clouds"
by Jinjun Chen 06 May '14

06 May '14

Call for Papers: IEEE Transactions on Cloud Computing Special Issue on "Big Data Computing on Clouds". Website: http://www.swinflow.org/si/tccbd.htm. Big data is an emerging paradigm applied to datasets whose size or complexity is beyond the ability of commonly used computer software and hardware tools. 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. As estimated by IDC, by 2020, about 40% data globally would be touched with Cloud Computing. Besides, Cloud Computing provides strong storage, computation and distributed capability in support of Big Data processing. Therefore, there is a strong demand to investigate various challenges about how to support Big Data processing by facilitating Cloud Computing potential. This special issue will focus on this challenging topic. *Topics* Original and unpublished high-quality research results are solicited to explore various challenging topics which include, but are not limited to: · Cloud Architecture for Big Data · Resource scheduling and SLA for Big Data on Cloud · Storage and computation management in Cloud for Big Data · Large-scale data intensive workflow in support of Big Data processing on Cloud · Multiple source data processing and integration on Cloud · Virtualisation and visualisation of Big Data on Cloud · Fault tolerance and reliability for Big Data processing on Cloud · MapReduce with Cloud for Big Data processing · Big data application workflow management on Cloud · Distributed file storage system with Cloud for Big Data · Inter-cloud technology for Big Data · Security, privacy and trust in Big Data processing on Cloud · Green, energy-efficient models and sustainability issues in Cloud for Big Data processing · Cloud infrastructure for social networking with Big Data · User friendly Cloud access for Big Data processing · Innovative Cloud data centre networking for Big Data · Wireless and mobility support in Cloud data centre for Big Data · Cloud and Big Data for Smart and Sustainable Cities *Schedule* Submission due date: November 15, 2014 Notification of acceptance: March 15, 2015 Submission of final manuscript: May 15, 2015 Publication date: 2nd Quarter, 2015 (Tentative) *Submission & Major Guidelines* The special issue invites original research papers that make significant contributions to the state-of-the-art in “Big Data Computing on Clouds”. The papers must not have been previously published or submitted for journal or conference publications. However, the papers that have been previously published with reputed conferences such as *IEEE BDSE 2014 (Big Data Science and Engineering - http://www.swinflow.org/confs/bdse2014/ <http://www.swinflow.org/confs/bdse2014/>*) could be considered for publication in the special issue if they contain significant number of "new and original" ideas/contributions along with more than 49% brand "new" material. Every submitted paper will receive at least three reviews. The editorial review committee will include well known experts in the area. Submissions must be directly submitted via the IEEE TCC submission web site at https://mc.manuscriptcentral.com/tcc-cs, and must follow instructions for formatting and length listed there. For additional information, please contact Jinjun.Chen(a)gmail.com. *Selection and Evaluation Criteria* - Significance to the readership of the journal - Relevance to the special issue - Originality of idea, technical contribution, and significance of the presented results - Quality, clarity, and readability of the written text - Quality of references and related work - Quality of research hypothesis, assertions, and conclusion *Guest Editors* Jinjun Chen (Contact Person), Jinjun.Chen(a)gmail.com, University of Technology Sydney, Australia Ivan Stojmenovic, ivan(a)site.uottawa.ca, University of Ottawa, Canada Irena Bojanova, ibojanova(a)umuc.edu, University of Maryland University College, USA

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CFP: [MR.BDI 2014] The 3rd International Symposium on MapReduce and Big Data Infrastructure, 03-05 December 2014, Sydney, Australia
by Nazanin Borhan 05 May '14

05 May '14

[We apologize if you receive multiple copies of this CFP.] Call for Papers – Deadline July 30, 2014 The 3rd International Symposium on MapReduce and Big Data Infrastructure (MR.BDI 2014) 03-05 December 2014, Sydney, Australia Co-located with the 4th IEEE International Conference on Big Data and Cloud Computing (BdCloud 2014 <http://www.swinflow.org/confs/bdcloud2014/>). Sponsored by Sponsored by IEEE TCSC <http://www.ieeetcsc.org/> Technical Area on Big Data and MapReduce http://www.swinflow.org/confs/mrbdi2014/ -------------------------------------------------------------------------------------------------------------------------------- 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 <http://www.swinflow.org/confs/mrbdi2013/> (Australia) and 2012 <http://www.swinflow.org/confs/bigdatamr2012> (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<http://kpnm.hnust.cn/confs/cgc2012/IEEECS_CPS_LaTeX_Letter_2Col.zip> or WORD <http://kpnm.hnust.cn/confs/cgc2012/IEEECS_CPS_8.5x11x2.zip>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<http://www.swinflow.org/confs/bdcloud2014/> and attend the conference to present the paper. ------------------------------------------------------------------------------------------------------------------------------ Publication of paper: All accepted papers will appear in the proceedings published by IEEE Computer Society (EI indexed). 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: July 30, 2014 Notification of Acceptance: September 25, 2014 Camera Ready Copies: October 15, 2014 Registration Due: October 15, 2014

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