@article{KrupitzerTemizerPrantletal.2020, author = {Krupitzer, Christian and Temizer, Timur and Prantl, Thomas and Raibulet, Claudia}, title = {An Overview of Design Patterns for Self-Adaptive Systems in the Context of the Internet of Things}, series = {IEEE Access}, volume = {8}, journal = {IEEE Access}, doi = {10.1109/ACCESS.2020.3031189}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-229984}, pages = {187384-187399}, year = {2020}, abstract = {The Internet of Things (IoT) requires the integration of all available, highly specialized, and heterogeneous devices, ranging from embedded sensor nodes to servers in the cloud. The self-adaptive research domain provides adaptive capabilities that can support the integration in IoT systems. However, developing such systems is a challenging, error-prone, and time-consuming task. In this context, design patterns propose already used and optimized solutions to specific problems in various contexts. Applying design patterns might help to reuse existing knowledge about similar development issues. However, so far, there is a lack of taxonomies on design patterns for self-adaptive systems. To tackle this issue, in this paper, we provide a taxonomy on design patterns for self-adaptive systems that can be transferred to support adaptivity in IoT systems. Besides describing the taxonomy and the design patterns, we discuss their applicability in an Industrial IoT case study.}, language = {en} } @article{KrupitzerEberhardingerGerostathopoulosetal.2020, author = {Krupitzer, Christian and Eberhardinger, Benedikt and Gerostathopoulos, Ilias and Raibulet, Claudia}, title = {Introduction to the special issue "Applications in Self-Aware Computing Systems and their Evaluation"}, series = {Computers}, volume = {9}, journal = {Computers}, number = {1}, issn = {2073-431X}, doi = {10.3390/computers9010022}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-203439}, year = {2020}, abstract = {The joint 1st Workshop on Evaluations and Measurements in Self-Aware Computing Systems (EMSAC 2019) and Workshop on Self-Aware Computing (SeAC) was 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 Ume{\aa}, Sweden on 20 June 2019. The goal of this one-day workshop was to bring together researchers and practitioners from academic environments and from the industry to share their solutions, ideas, visions, and doubts in self-aware computing systems in general and in the evaluation and measurements of such systems in particular. The workshop aimed to enable discussions, partnerships, and collaborations among the participants. This special issue follows the theme of the workshop. It contains extended versions of workshop presentations as well as additional contributions.}, language = {en} } @article{KaiserLeschRotheetal.2020, author = {Kaiser, Dennis and Lesch, Veronika and Rothe, Julian and Strohmeier, Michael and Spieß, Florian and Krupitzer, Christian and Montenegro, Sergio and Kounev, Samuel}, title = {Towards Self-Aware Multirotor Formations}, series = {Computers}, volume = {9}, journal = {Computers}, number = {1}, issn = {2073-431X}, doi = {10.3390/computers9010007}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-200572}, pages = {7}, year = {2020}, abstract = {In the present day, unmanned aerial vehicles become seemingly more popular every year, but, without regulation of the increasing number of these vehicles, the air space could become chaotic and uncontrollable. In this work, a framework is proposed to combine self-aware computing with multirotor formations to address this problem. The self-awareness is envisioned to improve the dynamic behavior of multirotors. The formation scheme that is implemented is called platooning, which arranges vehicles in a string behind the lead vehicle and is proposed to bring order into chaotic air space. Since multirotors define a general category of unmanned aerial vehicles, the focus of this thesis are quadcopters, platforms with four rotors. A modification for the LRA-M self-awareness loop is proposed and named Platooning Awareness. The implemented framework is able to offer two flight modes that enable waypoint following and the self-awareness module to find a path through scenarios, where obstacles are present on the way, onto a goal position. The evaluation of this work shows that the proposed framework is able to use self-awareness to learn about its environment, avoid obstacles, and can successfully move a platoon of drones through multiple scenarios.}, language = {en} }