Approach to Implementation of Configuration Process for Adaptive Software Systems based on Ontologies
DOI:
https://doi.org/10.47839/ijc.22.3.3234Keywords:
adaptive software systems, ontological approach, onto-oriented systems, methods of software adaptation, configuration of software systemsAbstract
Analysis of scientific research on the development of adaptive and self-adaptive software systems is conducted. It is established that the use of machine learning methods and feedback diagrams is an effective way to design and develop adaptive software. It is determined that the existing methods do not fully provide the possibility of dynamic changes and expansion of functional and graphic characteristics. The software adaptation process is designed based on the ontological model using the semantic decision-making mechanism. The proposed method allows us to dynamically determine the necessary system characteristics and perform software adaptation. Modification process takes into account the information about currently active device based on data about the needs and requirements of the user. Using the results of designing an abstract approach to software configuration modification, an experimental study of the speed of generating optimal system settings is conducted. According to the results of the experiment, it is established that the new method demonstrates 20% better indicators of the speed of generating software settings compared to classical approaches.
References
C. Szabo, B. Sims, T. Mcatee, R. Lodge and R. Hunjet, “Self-adaptive software systems in contested and resource-constrained environments: Overview and challenges,” IEEE Access, vol. 9, pp. 10711-10728, 2021, https://doi.org/10.1109/ACCESS.2020.3043440.
R. D. Lemos et al., “Software engineering for self-adaptive systems: A second research roadmap,” Software Engineering for Self-Adaptive Systems II, Berlin, Germany: Springer, 2013, pp. 1–32.
F. Macías-Escrivá, R. Haber, R. del Toro and V. Hernandez, “Self-adaptive systems: A survey of current approaches, research challenges and applications”, Expert Systems with Applications, vol. 40, no. 18, pp. 7267-7279, 2013. https://doi.org/10.1016/j.eswa.2013.07.033.
I. Gerostathopoulos, T. Vogel, D. Weyns and P. Lago, “How do we evaluate self-adaptive software systems? A ten-year perspective of SEAMS,” Proceedings of the 2021 International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS), Madrid, Spain, 2021, pp. 59-70, https://doi.org/10.1109/SEAMS51251.2021.00018.
D. Weyns, Software Engineering of Self-adaptive Systems, In Handbook of Software Engineering, Springer, 2019, pp. 399–443. https://doi.org/10.1007/978-3-030-00262-6_11.
C. Krupitzer, T. Temizer, T. Prantl, and C. Raibulet, “An overview of design patterns for self-adaptive systems in the context of the internet of things,” IEEE Access, vol. 8, pp. 187384–187399, 2020. https://doi.org/10.1109/ACCESS.2020.3031189.
T. R. D. Saputri and S.-W. Lee, “The application of machine learning in self-adaptive systems: A systematic literature review,” IEEE Access, vol. 8, pp. 205948-205967, 2020, https://doi.org/10.1109/ACCESS.2020.3036037.
O. Gheibi, D. Weyns, and F. Quin, “Applying machine learning in self-adaptive systems,” ACM Transactions on Autonomous and Adaptive Systems, vol. 15, no. 3, pp. 1–37, 2020. https://doi.org/10.1145/3469440.
D. Papamartzivanos, F. Gomez Marmol, and G. Kambourakis, “Introducing deep learning self-adaptive misuse network intrusion detection systems,” IEEE Access, vol. 7, pp. 13546–13560, 2019. https://doi.org/10.1109/ACCESS.2019.2893871.
L. Wang, “Search-based adaptation planning framework for self-adaptive systems,” Proceedings of the 2017 IEEE/ACM 39th International Conference on Software Engineering Companion (ICSE-C), Buenos Aires, Argentina, 2017, pp. 465-466, https://doi.org/10.1109/ICSE-C.2017.21.
J. Wan, Q. Li, L. Wang, L. He and Y. Li, “A self-adaptation framework for dealing with the complexities of software changes,” Proceedings of the 2017 8th IEEE International Conference on Software Engineering and Service Science (ICSESS), Beijing, China, 2017, pp. 521-524, https://doi.org/10.1109/ICSESS.2017.8342969.
Y. Li, Q. Li, L. Wang, W. Cheng and T. Wu, “ADAPT: An agent-based development toolkit and operation platform for self-adaptive systems,” Proceedings of the 2017 IEEE Conference on Open Systems (ICOS), Miri, Malaysia, 2017, pp. 53-58, https://doi.org/10.1109/ICOS.2017.8280274.
J. Mertz and I. Nunes, “On the practical feasibility of software monitoring: A framework for low-impact execution tracing,” Proceedings of the 2019 IEEE/ACM 14th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS), Montreal, QC, Canada, 2019, pp. 169-180, https://doi.org/10.1109/SEAMS.2019.00030.
E. Zavala, “Towards adaptive monitoring services for self-adaptive software systems,” Proceedings of the Service-Oriented Computing – ICSOC 2017 Workshops, 2018, pp. 357–362. https://doi.org/10.1007/978-3-319-91764-1_31.
L. Schölkopf, M.-M. Wolf, V. Hutmann, and F. Diermeyer, “Conception, development and first evaluation of a context-adaptive user interface for commercial vehicles,” Proceedings of the 13th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, 2021. https://doi.org/10.1145/3473682.3480256.
D. Nehurytsia and E. Sokolova, “User model in adaptive web-oriented system software interfaces,” Radio Electronic and Computer Systems, vol. 1, no. 65, pp.104-111, 2014.
I. Tvoroshenko, M. A. Ahmad, S. K. Mustafa, V. Lyashenko, A. R. Alharbi, “Modification of models intensive development ontologies by fuzzy logic,” International Journal of Emerging Trends in Engineering Research, vol. 8, no. 3, pp. 939–944, 2020. https://doi.org/10.30534/ijeter/2020/50832020.
A. Kindo, G. Kaladzavi, S. Malo, G. Camara, T. M. Y. Tapsoba and Kolyang, “Fuzzy logic approach for knowledge modeling in an ontology: A review,” Proceedings of the 2020 IEEE 2nd International Conference on Smart Cities and Communities (SCCIC), Ouagadougou, Burkina Faso, 2020, pp. 1-8, https://doi.org/10.1109/SCCIC51516.2020.9377335.
C. B. Nielsen, P. G. Larsen, J. Fitzgerald, J. Woodcock, and J. Peleska, “Systems of Systems Engineering,” ACM Computing Surveys, vol. 48, no. 2, pp. 1–41, 2015. https://doi.org/10.1145/2794381.
D. S. Santos, B. R. Oliveira, R. Kazman, and E. Y. Nakagawa, “Evaluation of systems-of-systems software architectures: State of the art and future perspectives,” ACM Computing Surveys, vol. 55, no. 4, pp. 1–35, 2022. https://doi.org/10.1145/3519020.
J. Axelsson, J. Fröberg, and P. Eriksson, “Architecting systems‐of‐systems and their constituents: A case study applying industry 4.0 in the construction domain,” Systems Engineering, vol. 22, no. 6, pp. 455–470, 2019. https://doi.org/10.1002/sys.21516.
A. Elhabbash, V. Nundloll, Y. Elkhatib, G. S. Blair, and V. S. Marco, “An ontological architecture for principled and automated system of systems composition,” Proceedings of the IEEE/ACM 15th International Symposium on Software Engineering for Adaptive and Self-Managing Systems,. 2020. https://doi.org/10.1145/3387939.3391602
D. Fedasyuk and I. Lutsyk, “Method of modification of self-adaptive software systems based on ontology,” Proceedings of the 2022 IEEE 16th International Conference on Advanced Trends in Radioelectronics, Telecommunications and Computer Engineering (TCSET), Lviv-Slavske, Ukraine, 2022, pp. 530-533, https://doi.org/10.1109/TCSET55632.2022.9766856.
D. Fedasyuk and I. Lutsyk, “Tools for adaptation of a mobile application to the needs of users with cognitive impairments,” Proceedings of the 2021 IEEE 16th International Conference on Computer Sciences and Information Technologies (CSIT), Lviv, Ukraine, 2021, pp. 321-324, https://doi.org/10.1109/CSIT52700.2021.9648702.
D. Fedasyuk and I. Lutsyk, “The use of ontology in the process of designing adaptive software systems,” Proceedings of the 2022 IEEE 17th International Conference on Computer Sciences and Information Technologies (CSIT), Lviv, Ukraine, 2022, pp. 503-506, https://doi.org/10.1109/CSIT56902.2022.10000528.
M. Moshref, R. Al-Sayyad, “Developing ontology approach using software tool to improve data visualization (Case study: Computer Network),” International Journal of Modern Education and Computer Science (IJMECS), vol. 11, no. 4, pp. 32-39, 2019. https://doi.org/10.5815/ijmecs.2019.04.04.
H. Razouki, “Security policy modelling in the mobile agent system,” International Journal of Computer Network and Information Security (IJCNIS), vol. 11, no. 10, pp. 26-36, 2019. https://doi.org/10.5815/ijcnis.2019.10.04.
Downloads
Published
How to Cite
Issue
Section
License
International Journal of Computing is an open access journal. Authors who publish with this journal agree to the following terms:• Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
• Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
• Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.