Industry Track: Call for Contributions
The extensive reliance on computing systems and networks raises numerous dependability challenges. Researchers and practitioners
face complex interdisciplinary issues, from manufacturing technology to hardware and software development, networking, integration
of complex systems, and cyber-security. The industry track provides a forum for interaction between industry and academia, and
presentation of the latest R&D and operational challenges, practical solutions, case studies, and field dependability data.
Industry contributions to the DSN community are invited to address dependability issues related to either the development process or
the operation of critical systems as seen from an industrial perspective.
The topics of interest target several aspects of dependable systems and networks:
- Hardware (e.g., VLSI, FPGA, and SOC)
- Technology (e.g., FinFET, nanotechnology, soft errors, and obsolescence of HW components)
- Networks (e.g., networks on a chip, optical networks, and wireless networks)
- Software (e.g., applications, middleware, and operating systems)
- Security (e.g., hardware and software cyber-security, and network security)
- Safety (e.g., autonomous critical systems/objects, car-to-X, plane-to-X systems)
- Field data (e.g. hardware and software fault/error data)
- Applications (e.g., embedded systems, drive by wire, and autonomous vehicles)
The Industry Track aims in particular at promoting and fostering discussion on advanced current work in an industrial context,
feedback from experiments, scalability issues regarding recent techniques, novel technology-related problems, etc.
The objective of this track is not to compete with the main DSN track, where finalized research and development work is presented,
but to give the members of industrial and academic communities the opportunity to discuss hot topics regarding the future of dependable
systems and networks, and to share experience among different industrial domains:
- Safety and Security of Autonomous and Intelligent Vehicles
- Fault-tolerance for Extreme Scale Systems
- Reliability for Aeronautics and Space Systems
- Dependability Issues in Software Defined Networks (SDN)
- Dependability of Cyber-physical Systems and Internet of Things
- Dependability Assessment of Complex Systems
- Dependability, Privacy, and Security of Clouds
- Dependability of Data Centers and Virtual Machines
- Dependability and Security of System Operation
- Trustworthiness of Smart Grids
- Dependability and Security of Big Data Systems
- Dependability of Blockchain and Financial Technology (Fintech) Systems
Important Dates
- Submission Deadline:
March 2, 2019 March 9, 2019
- Notification: March 30, 2019
- Camera Ready Materials: April 13, 2019
Submission Guidelines
Contributions can be in one of three formats:
- Position papers can focus on specific dependability aspects in practice, either a product or service offered to
the market or dependability analysis tools.
- Short papers should emphasize dependability challenges, practical solutions, trade-offs, strengths and weaknesses
of adopted solutions, lessons learned, and field and/or measured data.
All materials must be written in English, 1 page for position papers, 4 pages for short papers
(IEEE double-column format).
Papers must be submitted in their final form at EasyChair website.
Please note that at least one author must be from industry for the submission to be reviewed.
All accepted papers/abstracts will be published in the Proceedings of DSN2019 Industry Track and made available in IEEE Xplore.
Accepted materials will be presented in dedicated sessions.
Industrial Track co-Chairs
- Timothy Tsai, Nvidia, USA
- Tudor Dumitras, Univ. Maryland, USA
Contact
[email protected]
Track Program Committee:
- Michael Ciraula, AMD, USA
- Jean-Charles Fabre, LAAS, France
- Lelio Di Martino, Nokia Bell Labs, USA
- Kaustubh Joshi, AT&T Research, USA
- Tukaram Muske, TCS, India
- Santonu Sarkar, ABB, India
- Michael Sullivan, Nvidia, USA
- Long Wang, IBM Research, USA
- Alan Wood, Oracle, USA
- Keun Soo Yim, Google, USA