MRT-ICAC 2016 - International Workshop on Models@run.time for Self-aware Computing Systems

In order to most effectively use models at runtime, self-aware computing systems need increasingly powerful ways of observing their operational environment and their own performance and behavior and then building and refining their own models accordingly. An inherent principle of self-aware computing systems is having diverse feedback loops, which build a causal connection between the computing system and a reflective layer. The computing system is continously observed and, based on this, the system is able to update and modify its models to reason about its goals, context, operational environment and its own resources, decisions and actions.
To effectively and efficiently realize these feedback loops, models and especially modifiable and updatable models-AT-runtime are essential. The models-AT-run. time paradigm proposes to use runtime models as abstractions of the computing system for the purpose of more efficient reasoning upon both its runtime observations and learned knowledge. Hence, models-AT-runtime is especially looking for more innovative approaches to the causal connection between the system and the runtime model, with particular focus on a transaction concept for this causal connection for such issues as timing, roll-back ability and data-consistency.
The goal of this workshop is to provide a bridging podium for researchers working in the area of self-awareness, self-modelling, autonomous and organic computing, as well as self-adaptive and self-organizing systems with a focus on runtime representations that can be used by the system to reason about its goals, context, operational environment and its own resources, decisions and actions.
Topics of Interest
We are particularly interested in work covering the following non-exhaustive list of topics:
languagues and formalisms for runtime representations
approaches realizing the causal connection between the computing system and its reflective layer
applications and case studies involving runtime representations
a general discourse on
the need for and characteristics of runtime representations
the properties of causal connections (e.g., temporal properties, uncertainty, etc.)
interdisciplinary approaches to models-AT-run.time, as for example the mutual influence (or coercion) of socio-technical systems
How runtime models can address basic principles of areas such as game theory.
Distributed models-AT-run.time, i.e., having multiple, interacting systems, each having its own runtime model and in general, issues of models at runtime in large scale systems
Incomplete, partial models
Impacts of uncertainty
Approaches to real-time model-building, refinement
Relevant theory on transactions
Relevant lessons learned from bio-inspired, socially-inspired, unconventional systems
Modular models-AT-run.time, i.e., approaches to improve the modularity of models-AT-run.time systems for better reuse
Co-evolving models-AT-run.time, i.e., systematic approaches to synchronize multiple, interacting models-AT-run.time systems
For those papers focusing on executable models at runtime, we encourage the investigation of how the feedback from the systems are reflected in the executable models (so that they have causal (bi-)connections with the systems)