The joint workshops Evaluations and Measurements in Self-Aware Computing Systems (EMSAC) and the Workshop on Self-Aware Computing (SeAC) were held as part of the FAS* conference alliance in conjunction with the 16th IEEE International Conference on Autonomic Computing (ICAC) and the 13th IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO) in Umeå, Sweden at June 20, 2019. This was the first edition of the EMSAC workshop and the third of the SeAC workshop.
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 in the models@run-time community.
Self-aware computing systems are understood as having two main properties. They
- learn models, capturing knowledge about themselves and their environment (such as their structure, design, state, possible actions, and runtime behavior) on an ongoing basis;
- reason using the models (to predict, analyze, consider, or plan), which enables them to act based on their knowledge and reasoning (for example, to explore, explain, report, suggest, self-adapt, or impact their environment)
and do so in accordance with high-level goals, which can change. For this year edition, we want to have a special theme on IoT topics.
The SeAC workshop on self-aware computing 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.
The EMSAC workshop aims to address the issues and challenges concerning the evaluation of the quality (of the design and execution) of autonomous, self-aware and self-managing systems, as well as measurements concerning or related to the self-* or autonomous features of a system. A particular interest concerns the approaches which manage the trade-offs among various different quality attributes and focus on the autonomy of the system. Existing quality assurance and evaluation solutions should be adapted and improved to meet the evolving and dynamic requirements of self-aware and self-managing systems. Novel design and evaluation solutions are needed to face the complexity of autonomy and self-management, as well as to evaluate and measure the self-* mechanisms and the advantages they bring, also with respect to the effort spent for their development.
The workshop interests concern solutions proposed in various application domains which include cloud computing, smart systems, IoT, cyber-physical systems, systems-of-systems, robotics, autonomous driving, and social networks. This workshop aims to discuss the principles of quality assurance and evaluation/measurement for autonomous and self-managing systems and mechanisms, the current trends, the future issues and challenges to be addressed at design and run time. The workshop invites researchers and practitioners from industry and academic environments to share their solutions, ideas, visions, and doubts in the quality assurance and evaluation in autonomic computing. During the workshop, we enable discussions, partnerships, and collaborations among the software engineers interested in these themes.
The workshop started with a keynote by Betty H.C. Cheng from the Michigan State University on “A Requirements-Driven and Context-Aware Approach to Assurance of Autonomous Systems”. The keynote presented current developments towards a requirements-driven and context-aware autonomous system and overviewed a framework that supports run-time monitoring and adaptation of tests for evaluating whether an autonomous satisfies, or is even capable of satisfying, its requirements given its current execution context. Further, Betty Cheng described specific techniques that instantiate this framework, which apply a multidisciplinary approach to support requirements-based adaptive testing of an autonomous system at run time. The inspiring keynote raised fruitful discussion on the current state-of-the-art in testing and assurance under uncertainty in autonomous systems.
The first session was closed by Sona Ghahremani from the Hasso Plattner Institute at the University of Potsdam. She presented joint work with Holger Giese entitled “Performance Evaluation for Self-Healing Systems: Current Practice & Open Issues”. In their work, the authors provide a systematic literature review on approaches concerning the evaluation of self-healing systems. One of the main findings, which also raises discussions, was the miss of using real systems and demonstrators for evaluating the degree of self-healing in systems rather than simulation.
Peter Lewis from Aston University chaired the second session which was composed of five presentations of the EMSAC and SeAC workshops.
The second EMSAC workshop presentation was given by André Bauer from the University of Würzburg entitled “Systematic Search for Optimal Resource Configurations of Distributed Applications” was authored by André Bauer, Simon Eismann, Johannes Grohmann, Nikolas Herbst, and Samuel Kounev. The authors proposed and implemented a solution based on an adapted hill-climbing algorithm for finding all optimal configurations in a feasible time in micro-architecture approaches.
The third EMSAC presentation by Sven Tomforde from the University of Kassel raised discussions on the trade-off between stability and benefits of adaptation decisions for adaptive systems. In his presentation entitled “From “normal” to “abnormal” self-adaptation: A concept for determining expected adaptation efforts”, Sven Tomforde proposed a framework for the measurement of self-adaptivity and self-organization in complex systems based on the idea of identifying what is a normal and what is an abnormal adaptation.
Thereafter, the three presentations of the SeAC 2019 workshop followed. The first presentation hold by Vladimir Podolskiy from the Technical University of Munich focused on “Metrics for Self-Adaptive Queuing in Middleware for Internet of Things” authored by Peeranut Chindanonda, Vladimir Podolskiy, and Michael Gerndt. The paper presented several metrics for automating the scaling of message queuing subsystems and evaluated them on CPU-intensive and blocking I/O-intensive tasks.
The second SeAC presentation was hold by Johannes Grohman from the University of Würzburg about “Utilizing Clustering to Optimize Resource Demand Estimation Approaches”. In his joint work with Simon Eismann, André Bauer, Marwin Züfle, Nikolas Herbst, and Samuel Kounev, Johannes Grohmann proposes an approach for resource demand estimation which uses automated clustering for grouping training sets into groups of similar optimization behavior to tailor optimization towards certain groups of resource traces in a self-aware manner.
The presentation session of the SeAC and EMSAC workshop was closed by Cristina Abad from the Escuela Superior Politécnica del Litoral. The presentation entitled “Optimizing Cloud Caches For Free: A Case for Autonomic Systems with a Serverless Computing Approach”, authored by Xavier Andrade, Jorge Cedeno, Edwin F. Boza, Harold Aragón, Cristina L. Abad, and Jorge Murillo, discusses that serverless computing platforms can be leveraged to solve complex optimization problems that arise during self-tuning loops, and thus can be used to optimize resources in cloud caches, for free.
The presentations of EMSAC and SeAC were complemented by three presentations of the 1st IEEE International Workshop on Self-Protecting Systems (SPS). SPS is a forum for researchers working at the intersection of autonomic computing and cyber-security. The papers covered different aspects of self-protection: assuring security compliance in self adaptive systems, autonomous defense in Industrial Internet of Things, and performance evaluation of deep-learning for intrusion response.
We would like to thank Ingrid Nunes and Robert Birke, the workshop co-chairs of ICAC/SASO 2019 for their collaboration in the organization of the EMSAC and SeAC 2019 workshops. We thank the authors of the submitted papers, as well as the program committee members for their contributions. A special thank goes to André Bauer, the EMSAC 2019 workshop publicity chair, as well as to Norbert Schmitt, the SeAC 2019 workshop publicity chair.
Benedikt Eberhardinger, Ilias Gerostathopoulos, Christian Krupitzer, and Claudia Raibulet (EMSAC organizers)
Christian Krupitzer, and Peter Lewis (SeAC organizers)