Browsing by Author "Aksit, M."
Now showing 1 - 3 of 3
- Results Per Page
- Sort Options
ArticlePublication Metadata only Availability analysis of software architecture decomposition alternatives for local recovery(2017) Sözer, Hasan; Stoelinga, M.; Boudali, H.; Aksit, M.; Computer Science; SÖZER, HasanWe present an efficient and easy-to-use methodology to predict—at design time—the availability of systems that support local recovery. Our analysis techniques work at the architectural level, where the software designer simply inputs the software modules’ decomposition annotated with failure and repair rates. From this decomposition, we automatically generate an analytical model (a continuous-time Markov chain), from which an availability measure is then computed, in a completely automated way. A crucial step is the use of intermediate models in the input/output interactive Markov chain formalism, which makes our techniques efficient, mathematically rigorous, and easy to adapt. In particular, we use aggressive minimization techniques to keep the size of the generated state spaces small. We have applied our methodology on a realistic case study, namely the MPlayer open-source software. We have investigated four different decomposition alternatives and compared our analytical results with the measured availability on a running MPlayer. We found that our predicted results closely match the measured ones .ArticlePublication Open Access Data fusion analysis and synthesis framework for improving disaster situation awareness(MDPI, 2023-09) Aksit, M.; Say, Hanne; Eren, Mehmet Arda; de Camargo, V. V.; Say, Hanne; Eren, Mehmet ArdaTo carry out required aid operations efficiently and effectively after an occurrence of a disaster such as an earthquake, emergency control centers must determine the effect of disasters precisely and and in a timely manner. Different kinds of data-gathering techniques can be used to collect data from disaster areas, such as sensors, cameras, and unmanned aerial vehicles (UAVs). Furthermore, data-fusion techniques can be adopted to combine the data gathered from different sources to enhance the situation awareness. Recent research and development activities on advanced air mobility (AAM) and related unmanned aerial systems (UASs) provide new opportunities. Unfortunately, designing these systems for disaster situation analysis is a challenging task due to the topological complexity of urban areas, and multiplicity and variability of the available data sources. Although there are a considerable number of research publications on data fusion, almost none of them deal with estimating the optimal set of heterogeneous data sources that provide the best effectiveness and efficiency value in determining the effect of disasters. Moreover, existing publications are generally problem- and system-specific. This article proposes a model-based novel analysis and synthesis framework to determine the optimal data fusion set among possibly many alternatives, before expensive implementation and installation activities are carried out.Book ChapterPublication Metadata only Guiding architects in selecting architectural evolution alternatives(Springer Science+Business Media, 2011) Ciraci, S.; Sözer, Hasan; Aksit, M.; Computer Science; SÖZER, HasanAlthough there exist methods and tools to support architecture evolution, the derivation and evaluation of alternative evolution paths are realized manually. In this paper, we introduce an approach, where architecture specification is converted to a graph representation. Based on this representation, we automatically generate possible evolution paths, evaluate quality attributes for different architectural configurations, and optimize the selection of a particular path accordingly. We illustrate our approach by modeling the software architecture evolution of a crisis management system.