ASBDA 2017 - International Workshop on Autonomic Systems for Big Data Analytics (ASBDA 2017)

International Workshop on Autonomic Systems for Big Data Analytics (ASBDA 2017)
Co-located with IEEE ICACC 2017 and IEEE SASO 2017
September 18-22, 2017, Tucson, Arizona, USA
Workshop web page: http://www.ce.uniroma2.it/asbda2017/
ICACC web page: http://autonomic-conference.org/iccac-2017/
*** Journal special issues: ***
Cluster Computing
Future Generation Computing Systems
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In the Big Data ecosystem, the velocity and volume at which data arrive for processing represent two challenging issues to be addressed in the design of systems, frameworks and applications. These challenges are exacerbated by increasingly demanding Quality of Service requirements that must be met despite workload variability or changes occurring in the execution environment, which might leverage on multi-clouds or edge computing resources. Due to the presence of multiple layers that compose a data analytics platform, the variable resource requirements across the layers and the intrinsic complexity of each layer, human-assisted control or manual configuration is unrealistic. Autonomic systems enable to rule the complexity of managing data analytics platforms and integrate monitoring, planning, and execution capabilities so to satisfy some utility goal (e.g., maximize performance, reduce power wastage, guarantee reliable processing). The variety and complexity of Big Data systems, tha
t include data center and cloud resource managers, distributed storage systems, frameworks for batch, micro-batch and data stream processing, demand for specific autonomic solutions to address the multiple facets and foster novel interdisciplinary approaches.
This workshop intends to promote a community-wide discussion to identify and find suitable solutions that enable autonomic features in systems, frameworks, and applications for Big Data analytics. We are looking for papers that present new techniques, introduce new methodologies, propose new research directions, or discuss research challenges and report latest efforts from academia and industry that include (but are not limited to) the following topics:
- Autonomic provisioning of Big Data applications in Cloud, distributed Cloud and edge computing environments
- Autonomic resource management and admission control for Big Data systems
- Autonomic data caching, movement and partitioning for Big Data systems
- Customizations and extensions of existing software infrastructures and platforms to support autonomic Big data analytics
- Elastic techniques to cope with bursty workloads and varying resource demands
- Runtime reconfiguration strategies to cope with highly dynamic execution environments
- Self-adaptive scheduling and placement strategies for Big Data systems on clusters, Clouds, and distributed Clouds
- Applications and case studies of autonomic Big Data analytics in various domains, including astrophysics, biology, climate change, healthcare, Internet of Things, Smart Cities, and social networks
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Submission Guidelines
We call for original and unpublished papers describing research results, experience, and visions. They can be in one of the two formats: a full paper that should not exceed 8 pages double column, including figures, tables, references and appendices or 4-page position paper. Submitted manuscripts should be in the standard IEEE format for conference proceedings (see formatting templates for details: http://www.ieee.org/conferences_events/conferences...).
Papers should be submitted as PDF files via Easychair at https://easychair.org/conferences/?conf=asbda2017.
At least one author of each accepted paper is required to attend the workshop and present the paper. Presented papers will be included in the workshop proceedings volume that will be published by IEEE and included in the IEEE Xplore Digital Library.
*** Special Issue ***
A special issue on Cluster Computing (Springer) will include an extension of the best papers of all the workshops that will be held in conjunction with IEEE ICCAC 2017.
Furthermore, authors of selected papers on data stream processing will be invited to submit an extended version to a special issue on Future Generation Computing Systems (Elsevier).
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Important Dates
Submission deadline: June 9, 2017
Notification of acceptance: July 7, 2017
Camera-ready submission: July 21, 2017
Workshop date: September 18-22, 2017
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Committees
Program Co-Chairs
Valeria Cardellini, University of Rome Tor Vergata, Italy
Manish Parashar, Rutgers University, USA
Publicity and Web Chair
Matteo Nardelli, University of Rome Tor Vergata, Italy
Technical Program Committee
Sara Bouchenak, INSA Lyon, France
Rodrigo N. Calheiros, University of Western Sydney, Australia
Emiliano Casalicchio, Blekinge Institute of Technology, Sweden
Javier Diaz-Monte, Rutgers University, USA
Pooyan Jamshidi, Imperial College, UK
Song Jiang, Wayne State University, USA
Jayaram K.R, IBM Research, USA
Vana Kalogeraki, Athens University of Economics and Business, Greece
Odej Kao, TU Berlin, Germany
Ioannis Konstantinou, National Technical University of Athens, Greece
Francesco Lo Presti, University of Rome Tor Vergata, Italy
Gabriele Mencagli, University of Pisa, Italy
Matteo Nardelli, University of Rome Tor Vergata, Italy
Bogdan Nicolae, Huawei Research Europe, Germany
Vladimir Vlassov, KTH Royal Institute of Technology, Sweden
Yinglong Xia, Huawei Research America, USA
Weikuan Yu, Florida State University, USA