During the past decade, many different research communities have explored the aspects of self-awareness in computing systems, each from their own perspective. Relevant work can be found in different areas including autonomic computing, self-adaptive and self-organizing software and systems, machine learning, artificial intelligence and multi-agent systems, organic computing, context- and situation-aware systems, reflective computing, model-predictive control, as well as work from the models@run-time community.
The workshop on self-aware computing (SeAC) provides a forum to foster interaction and collaborations between the respective research communities, raising the awareness about related research efforts and synergies that can be exploited to advance the state of the art. The workshop was initiated by the 2015 Dagstuhl Seminar 15041 on model-driven algorithms and architectures for self-aware computing systems, which brought together 45 international experts. As proposed by the seminar and documented in a recent Springer book on the topic, self-aware computing systems are understood in a broad sense seeking to integrate the different ways in which this term is used in the interdisciplinary research landscape.
Topics of Interest
- Fundamental science and theory of self-aware computing systems
- Levels and aspects of self-aware computing systems
- Architectures for individual and collective systems
- Methods and algorithms for model learning (self-modeling) and reasoning
- Self-adaptation in individual and collective systems
- Synthesis and verification Metrics and benchmarks
- Transition strategies for increasing self-awareness in existing systems
- Open challenges and future research directions
- Applications and case studies: cloud computing, cyber-physical systems, data centers, dependable computing, industrial internet / industry 4.0, internet of things, mobile computing, service-oriented systems, smart buildings, smart city, smart grid / energy management, smart factory, traffic management, autonomous robotics, and space applications.
The workshop participants will be selected based on their experience and ideas related to the field of self-aware computing. There are two ways to participate: i) present a talk without a respective paper published in the workshop proceedings, ii) submit a paper to be presented at the workshop and published in the workshop proceedings.
We solicit the following types of contributions:
- Talk extended abstract limited to 1 page (without formatting restrictions)
- Full paper limited to 8 pages (double column, IEEE format)
- Short paper limited to 6 pages (double column, IEEE format)
Contributions in the 1st category may have already been (partially) presented at other events or in publications. Contributions in the 2nd and 3rd category (technical papers) must represent original and unpublished work that is not currently under review. Full papers may report on original research, lessons learned from realizing an approach, or experiences on transferring a research prototype into practice. Short papers may report on work-in-progress or present a vision or position motivating the community to address new challenges.
Papers will be reviewed by at multiple PC members and judged on originality, significance, interest, correctness, clarity, and relevance to the broader community. At least one author of each accepted submission is required to attend the workshop.
Technical papers will be published by IEEE Computer Society Press and made available as a part of the IEEE Xplore Digital Library. In addition, papers will be part of the ICAC conference proceedings with ISBN number.
Technical papers should follow the double column, IEEE format and need to be submitted electronically via EasyChair. Extended abstracts need to be submitted as “abstract only” submissions via EasyChair. Further submission instruction will follow. See Important Dates for submission deadlines.
- Samuel Kounev and Nikolas Herbst, University of Würzburg, Germany
- Martina Maggio, Lund University, Sweden