Doctoral Symposium on Foundations and Applications of Self-* Systems (FAS*W)

There is a doctoral symposium at the SASO  conference this year.

Call For Doctoral Symposium Submissions Doctoral Symposium on Foundations and Applications of Self-* Systems (FAS*W)

Augsburg, Germany, September 12 & 16, 2016 EXTENDED DEADLINES: Abstract Submission due: June 12, 2016 Paper Submission due: June 20, 2016 @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.

Submission Instructions

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.

Review Process

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.

Invited Talk

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

Important Dates (Extended)

Abstract Submission due (extended): June 12, 2016 Paper Submission due (extended): June 20, 2016 Notifications due: July 10, 2016 Camera ready version due: July 24, 2016 Conference date: September 12-16, 2016

Contact Information

For any further information, please contact the Doctoral Symposium chairs: Pradeep Murukannaiah Department of Computer Science North Carolina State University Raleigh, NC, 27606, USA Dr. Ingo Scholtes Chair of Systems Design ETH Zurich CH-8092 Zurich Switzerland

So Sad Today: Personal Essays

Melissa Broder (2016)

The story of an obsessive personality that makes one glad not to share similar traits. It’s strange how, in someone else’s mind, trivial things can assume enormous proportions; amazing how emotions can be felt differently than one would expect; strange that they can be felt in different ways simultaneously. I think this book is best read both as a story of survival – and as a warning in case you meet someone like the author and struggle to connect with them.

2/5. Finished Wednesday 27 April, 2016.

(Originally published on Goodreads.)

Small Is Beautiful

Ernst F. Schumacher (1973)

One of the founding texts of the environmental movement, and one that asks profound questions about the relationships between humanity and our environment. There are some great ideas about the nature and place of economics in deciding priorities for human investment and lifestyle. But taken as whole this isn’t a book that’s aged well.

Why not? I think there are three essential reasons. Firstly, there’s a rather declamatory style to the presentation that presents as certainties things that are actually rather questionable. For example, Schumacher dismisses statistics: “and of course, nothing can be proven with statistics”. I beg to disagree: in any physical or life science, one can only prove things with statistics, since there will always be noise and error in any set of observations that can only be properly analysed and quantified statistically.

Secondly, to continue from above, Schumacher is surprisingly dismissive of science as a useful cultural basis. He identifies six “large ideas” that – he claims – stem from the humanities and offer a broader and firmer foundation for living than any scientific ideas. And what do these “large ideas” consist of? Well at least two of them (evolution and natural selection) belong firmly within science after all; two more (class struggle and positivism) have been largely discredited, while another (Freudian sub-consciousness) has been changed beyond recognition; and the last (relativism), to the extent that it allows multiple opinions as to the Truth (with a capital T), is maybe the only one left standing – and can hardly be argued not to rest at least in part on scientific ideas of uncertainty and progressive refinement.

But the third problem is the most interesting. It seems to me that many of Schumacher’s arguments are logical and well-supported by evidence – but have been proven wrong by events. A good example is his (again rather declamatory) assertion that economic growth must always be underpinned by increased energy consumption, which must necessarily come up against resource limitations. A plausible argument: but recent history shows growth decoupling from energy, with energy per unit GDP plummeting, driven in large measure by the rise of the service and digital economies. Schumacher could have dealt with the former, even if we accept he could have known nothing of the latter. But this lack of knowledge about future developments is not something that will ever disappear, and it renders his style of sweeping large-scale pronouncements permanently suspect.

It is always dangerous to make predictions, especially about the future (as Yogi Berra once observed). That doesn’t mean we shouldn’t continue to try to do so, but nor is it an excuse to dress up opinion as fact, or to claim that certain conclusions are inescapable and irrefutable. We won’t get to the truth by literary means, and we need to accept that we continually over-estimate how quickly things will change when extrapolating from the present – and continually under-estimate how different from our predictions the long-term future will be. That’s a level uncertainty that frustrates those looking for a single-issue “hook” on which to hang concrete action, but is nevertheless the world we actually live in.

2/5. Finished Monday 4 April, 2016.

(Originally published on Goodreads.)

Wastelands: Stories of the Apocalypse (Wastelands #1)

John Joseph Adams (2008)

3/5. Finished Monday 29 February, 2016.

(Originally published on Goodreads.)

Thing Explainer: Complicated Stuff in Simple Words

Randall Munroe (2015)

Complicated stuff explained in simple words.

It’s hard to decide how to classify Thing explainer. On the one hand it should be a children’s book: I once owned a book called “What makes it go?” that did a similar job. And Monroe does an excellent job at explaining things that children will want to know about: the US space team’s up-goer five, Earth’s past, the Big thing tiny hitter, and more. And also some things they hopefully won’t want to know too much about, like the Machine for burning cities.

But there’s also something of a conceit to the book, in that it’s limiting its vocabulary for effect and not simply for clarity of explanation. That makes some things a lot harder than they need to be, and marks the book out as really not for children at all.

That being said, it’s extremely enjoyable, as well-written and well-illustrated as What If?: Serious Scientific Answers to Absurd Hypothetical Questions and the rest of xkcd. Definitely to be recommended.

4/5. Finished Sunday 28 February, 2016.

(Originally published on Goodreads.)