Head of the RiSING Research Unit at FBK CREATE- NET, Italy and Decenter (http://www.decenter-project.eu/) co-ordinator.
More Details can be found here
Call for Workshop Paper
Today, huge amount of data is being generated by the Internet of Things (IoT), such as smartphones, sensors, cameras, cars and robots. In order to process the generated data, there exist Big Data platforms ( such as Hadoop and Spark ). Conventionally, they are deployed in centralised Data Centers, which, however, fails short of addressing time-critical requirements of the applications due to high latency between the Edge, where the data are generated and the Data Centers where they are processed. The emerging Edge/Fog computing paradigm promises to solve this problem by seamlessly integrating hardware and software resources across multiple computing tiers, from the Edge to the Data Center/Cloud. Since computing resources at the Edge may be power and capacity constrained, it is necessary to invent new lightweight platforms and techniques that seamlessly interact, sense, execute and produce results with very low latency, while at the same time address other high-level requirements of applications, such as security and privacy.
Regarding these problems there are many challenges that must be addressed with the invention of new architectures, methods, algorithms and solutions that:
- Integrate and process data from underlying IoT platforms and services
- Smartly select data streams for processing
- Address the 4 “V” of the Big Data problem: volume, variety, velocity and veracity
- Improve the energy efficient management of resources and tasks processing
- Address the QoS and time-critical aspects of smart applications
- Facilitate intelligent integration of information arising from various sources
- Address the requirements of very dynamic Big Data pipelines (e.g. moving smartphones, sensors, cars, robots with dynamically changing requirements for processing)
- Provide orchestration methods and scheduling policies that address dependability, reliability, availability and other high-level application requirements
- Adequately address the inherent variability of resources from the Edge to the Data Centers
- Provide new architectures which use the powerful computing resources of Data Centers, while at the same time providing optimal QoS to applications
- Address the decentralisation aspects through the use of Blockchain-based Smart Contracts and Oracles
- Implement distributed Artificial Intelligence methods from the Edge to the Data Center/Cloud
Special Issue of the Software: Practice and Experience journal
Selected best papers will be invited to submit to a Special Issue of the Software: Practice and Experience journal.
The workshop aims to bring together scientists and practitioners interested in the intricacies of the implementation of large-scale Big Data pipelines. Our intention is to discuss various problems, challenges, new approaches and technologies addressing this hot new area of research. The idea is to shortlist the most challenging problems, to shape future directions for research, foster the exchange of ideas, standards and common requirements. We look for high quality work that addresses various aspects of the investigated problem.
Submitted manuscripts should be structured as technical papers and may not exceed six (6) single-spaced double-column pages using 10-point size font on 8.5 × 11 inch pages (IEEE conference style), including figures, tables, and references. See IEEE style templates at this page for details.
Electronic submissions must be in the form of a readable PDF file. All manuscripts will be reviewed by the Program Committee and evaluated on originality, relevance of the problem to the conference theme, technical strength, rigor in analysis, quality of results, and organization and clarity of presentation of the paper.
Submitted papers must represent original unpublished research that is not currently under review for any other conference or journal. Papers not following these guidelines will be rejected without review and further action may be taken, including (but not limited to) notifications sent to the heads of the institutions of the authors and sponsors of the conference.
Presentation of an accepted paper at the workshop is a requirement of publication. Any paper that is not presented at the conference will not be included in the proceedings.
Paper Submission : September 20th, 2019
Notification to Authors : October 14th, 2019
Workshop camera-ready : October 28th, 2019
Easychair Submission Link: https://easychair.org/my/conference?conf=bigdatapipelines2019
Vlado Stankovski, University of Ljubljana, Slovenia
Rajkumar Buyya, CLOUDS Lab, The University of Melbourne, Australia
Shashikant Ilager, CLOUDS Lab, The University of Melbourne, Australia
Program Committee Members
Yogesh Barve, Vanderbilt University, USA
Emiliano Casalicchio, Blekinge Institute of Technology and Sapienza University of Rome, Italy
Kyle Chard, University of Chicago and Argonne National Lab, USA
Jānis Grabis, Riga Technical University, Latvia
Peter Kacsuk, Hungarian Academy of Sciences, Hungary
Dragi Kimovski, University of Klagenfurt, Austria
Marta Patiño-Martínez, Universidad Politécnica de Madrid, Spain
Dana Petcu, West University of Timisoara, Romania
Francisca Pérez, Universidad San Jorge, Spain
Deepak Poola Chandrashekar, IBM, India
Yogesh Simmhan, Indian Institute of Science, India
Heru Suhartanto, Universitas Indonesia, Indonesia
Huaming Wu, Tianjin University, China
Minxian Xu, Shenzhen Institutes of Advanced Technology, China
Aleš Zamuda, University of Maribor, Slovenia
Vlado Stankovski, Ph.D.
Associate Professor of Computer Science
Distributed and Cloud Computing
University of Ljubljana, Slovenia
Email: [email protected]
Phone: +386 41 200 565
Dr. Rajkumar Buyya, Redmond Barry Distinguished Professor
Director, Cloud Computing and Distributed Systems (CLOUDS) Lab
School of Computing and Information Systems
The University of Melbourne
Email: [email protected]
Shashikant Ilager, Research Scholar
CLOUDS Lab, School of Computing and Information Systems
The University of Melbourne
Email – [email protected]