The call for participation in the FAS 2016 doctoral symposium is now open.
FASW 2016 (SASO and ICCAC) Call For Doctoral Symposium Submissions Doctoral Symposium on Foundations and Applications of Self- Systems (FAS*W)Augsburg, Germany, September 12 & 16, 2016 http://fasstar2016.informatik.uni-augsburg.de/ http://iccac2016.se.rit.edu/ http://uni-augsburg.de/saso2016 @SASO2016Conf
Foundations and Applications of Self Systems (FAS) is the umbrella for two closely related but independent conferences, the International Conference on Self-Adaptive and Self-Organizing Systems (SASO) and the International Conference on Cloud and Autonomic Computing (ICCAC). The FAS Doctoral Symposium provides an international forum for PhD Students working in research areas addressed by FAS. In this forum, PhD students will get unique opportunities to subject their research to the scrutiny of external experts, gain experience in the presentation of research, connect to peers and experts addressing similar problems, and get advice from a panel of internationally leading researchers. Different from the technical tracks of the conference, the FAS* Doctoral Symposium focuses on the specific needs of young researchers at the beginning of their career. As such, particular emphasis will be placed on a critical and constructive feedback that shall help participants to successfully conclude their PhD studies.
PhD students working in any area addressed by the FAS conferences are invited to submit a Doctoral Symposium paper in which they describe the key motivation and objectives of their research project, and reflect on the methodology as well as the current status of their PhD studies. Complementing the thematic focus of FAS, we particularly solicit contributions in the following areas:
- Engineering of self-organizing and self-adaptive systems. We solicit theoretical and applied works addressing fundamental principles underlying self-organizing systems, as well as methods that allow to quantify, model and reproduce the self-* characteristics of complex systems in biological, social, physical and technical systems. Examples include mechanisms underlying distributed decision- making and collective intelligence, software engineering challenges in self-adaptive systems, as well as general application of self-* principles in the engineering of technical systems.
- Complex Cyber-physical and socio-technical systems. We welcome contributions that apply self-* principles to address challenges in the design of complex cyber- physical and socio-technical systems. Particular examples include smart grid infrastructures, sensor networks, opportunistic networking scenarios, as well as large-scale social information systems. Works addressing challenges such as the security, privacy and anonymity of users, or mechanisms to prevent censorship, manipulation or unfairness in socio-technical systems are especially welcome. We further solicit works on socio- technical and socio-economic challenges in P2P systems, such as the design of incentive, trust and reputation mechanisms.
- Self-* approaches in Massive-Scale Decentralized Systems. Works in this area use self-* approaches to address challenges in the design and operation of massive scale decentralized systems. Examples include Peer-to-Peer technologies, as well as overlay topology management schemes. We are further interested in decentralized data mining and machine learning approaches, as well as decentralized approaches to monitor, model and adapt distributed systems. Works using self-* principles to address the inherent challenges in the design of massive-scale systems with unreliable and heterogeneous are of particular interest.
- Autonomic Computing Systems. Here we are interested in all works addressing the self-configuration, self-optimization and self-adaptation of cloud computing services, data centers and general distributed computing systems. Examples for questions addressed in this area include the monitoring and modeling of cloud services, the design of efficient resource allocation mechanisms, the application of data mining and machine learning techniques to analyze and predict the behavior of technical systems, as well as the characterization of distributed computing workloads.
- Application of Self-* in Robotics and Spatial Computing, Finally, we welcome contributions using self-* principles in the areas of robotics, swarm robotics and spatial computing. Here, examples for works of interest include environmental modeling and perception, machine vision, and self-adaptation mechanisms in robotics, distributed coordination and collective intelligence in multi- robot systems, as well as novel paradigms for the programming of autonomous, spatially distributed entities.
Submissions should have a length of max. six pages and be formatted according to the IEEE Computer Society Press proceedings style guide. Authors should submit their papers using the EasyChair installation of the main conference, which is available at:
Please note that only single-author submissions are accepted, which focus on the topic of the doctoral work. The name of the supervisor (« supervised by ... ») should be clearly marked below the author’s name in the paper. Submissions should further adhere to the following structure:
- Motivation: motivate the open problem that you want to address and briefly summarize existing approaches along with their deficiencies.
- Objectives: describe the key objectives of your PhD project and argue how achieving them will solve the open problem outlined in the motivation.
- Methodology: outline what methodology you will adopt to meet the objectives of your project. Clearly state on what existing works your work will build.
- Research Plan: describe what preliminary results – if any – you have already achieved and summarize your plans for future work. Please add a rough schedule that allows to judge whether your research plan is feasible.
Authors of accepted papers shall prepare a final, camera ready version of the paper, taking into account all feedback from reviewers, and formatted according to the IEEE Computer Society Press proceedings style guide. Doctoral Symposium papers will be advertised in the final program, and will be submitted to IEEE Xplore as part of the SASO proceedings. Papers will also be made available in the IEEE Digital Library.
Each submission will be reviewed by at least two Doctoral Symposium experts (see list below) that cover the different areas of interest of the conference. Submissions will be evaluated based on their relevance to FAS*, the motivation and quality of the proposed research, as well as the suitability of the chosen methodology.
Authors of accepted papers will have different opportunities to present their project at the conference. Besides a full presentation during the PhD Symposium session, an “Elevator Pitch Session” will be organized during the main conference, where authors get the chance to briefly showcase their research. In addition, the Best Doctoral Symposium paper will be selected and the award will be presented during the main conference. Finally, selected authors will have the additional chance to present their work via a poster in the poster session of the main conference.
To be announced
Doctoral Symposium Experts
- Ozalp Babaoglu – University of Bologna, IT
- Jacob Beal – BBN Technologies, USA
- Kurt Geihs – Universitaet Kassel, DE
- Tom Holvoet – KU Leuven, BE
- Manish Parashar – Rutgers University, USA
- Jeremy Pitt – Imperial College London, UK
- Mark Jelasity – University of Szeged, HU
- Burkhard Stiller – University of Zurich, CH
- Giuseppe Valetto – Fondazione Bruno Kessler, Trento, IT
- Salim Hariri – University of Arizona, USA
- Simon Dobson – University of St Andrews, Scotland, UK
- Antonio Bucchiarone - Fondazione Bruno Kessler, Trento, IT
To be completed
Abstract Submission due: May 29, 2016 Paper Submission due: June 12, 2016 Notifications due: July 10, 2016 Camera ready version due: July 24, 2016 Conference date: September 12-16, 2016
For any further information, please contact the Doctoral Symposium chairs: