Ontological model for data processing organization in information and communication networks
Keywords:information and communication network, data processing system, ontology, model, network operator, analysis, scaling, class
The functioning of modern information and communication networks is impossible without data processing. With the emergence of new network services, the amount of information that needs to be processed increases, while the requirements to the data processing quality become more and more stringent. Therefore, the problem of designing and maintaining a scalable data processing system with a flexible quality of service management is becoming more and more important for a network operator. Such data processing systems have a complex internal structure with many interrelated parameters, which makes them difficult to analyze, manage, and expand. This study proposes to use an ontological model to store, represent, and manipulate the information in the operator’s data processing system. The ontological model allows to structure and systematize the data of an information processing system, and transparently reflects the relationships between the parameters of the system to simplify its analysis and scaling. The proposed ontology of a data processing system consists of three related subsystems. The paper describes the proposed ontological model and additionally analyzes the sources of information that needs to be processed in the information and communication network.
The law of Ukraine About telecommunications [Online]. Available: https://zakon.rada.gov.ua/laws/show/1280-15#Text). Accessed on: 11 Oct. 2020.
Jan Harrington, The Relational Data Model, 2009. doi: 10.1016/B978-0-12-374730-3.00005-X.
Antonio Badia, Relational, Object-Oriented and Object-Relational Data Models, 2006. doi: 10.4018/9781591405603.ch088.
John Mariani and Tom Rodden, A Model for Schema Evolution in Object-Oriented Database Systems, 1994.
Nicola Guarino, Daniel Oberle, and Steffen Staab, What Is an Ontology?, 2009. doi: 10.1007/978-3-540-92673-3_0.
L.S. Globa, R.L. Novogrudska, and A.V. Koval, “Ontology Model of Telecom Operator Big Data”, Proceedings of IEEE International Black Sea Conference on Communication and Netwoorking (BlackSeaCom), 1-5, 2018. doi:10.1109/ BlackSeaCom. 2018.8433710
C. Villalonga et al., “Mobile Ontology: Towards a Standardized Semantic Model for the Mobile Domain”, Proceedings of the 1st International Workshop on Telecom Service Oriented Architectures (TSOA 2007) at the 5th International Conference on Service-Oriented Computing, Vienna, Austria, September 17, 2007, pp. 248–257.
Qiao Xiuquan, Li Xiaofeng, and Chen Junliang, Telecommunications Service Domain Ontology: Semantic Interoperation Foundation of Intelligent Integrated Services, 2012. doi: 10.5772/36794.
View on 5G Architecture: 5G PPP Architecture Working Group [Online]. Available: https://5g-ppp.eu/wp-content/uploads/2019/07/5G-PPP-5G-Architecture-White-Paper_v3.0_PublicConsultation.pdf. Accessed on: 20 Sept. 2020.
Data Center Market and Technology Trends Power Electronics presentation [Online]. Available: https://www.slideshare.net/Yole_Developpement/data-center-market-and-technology-trends-power-electronics-presentation-held-at-apec-2016-from-yole-dveloppement. Accessed on: 18 Oct. 2020.
Qiu Yeliang, Jiang Congfeng, Wang Yumei, Ou Dongyang, Li Youhuizi, and Wan Jian, Energy Aware Virtual Machine Scheduling in Data Centers. Energies, 2019. doi: 12. 646. 10.3390/en12040646.
F. Armenta-Cano et al., “Min_c: Heterogeneous Concentration Policy for Power Aware Scheduling. Trudy ISP RAN”, Proc. ISP RAS, vol. 27, issue 6, 2015, pp. 355–380.
Hosseinimotlagh Seyedmehdi, Khunjush Farshad, and Hosseinimotlagh Seyedmahyar, A Cooperative Two-Tier Energy-Aware Scheduling for Real-Time Tasks in Computing Clouds, 2014, pp. 178–182. doi: 10.1109/PDP.2014.91.
Mohammad Aldossary and Karim Djemame, Performance and Energy-Based Cost Prediction of Virtual Machines Auto-Scaling in Clouds, 2018.
P.P. Vorobienko, L.A. Nikityuk, and P.I. Reznichenko, Communication and information networks, Approved by the Ministry of Education and Science of Ukraine as a textbook for students of higher education institutions. Kyiv, 2010.
Talapko Domagoj, Telecom datacenter power infrastructure availability comparison of DC and AC UPS, 2012, pp. 1–5. doi: 10.1109/INTLEC.2012.6374509.
Benzekki Kamal, El Fergougui Abdeslam, El Belrhiti El Alaoui Abdelbaki, Software-defined networking (SDN): A survey. Security and Communication Networks, 2017. doi: 9. 10.1002/sec.1737.
Zhang Tianzhu, NFV Platform Design: A Survey, 2020.
Big Data for business. Big Data from Kyivstar [Online]. Available: https://kyivstar.ua/uk/business/products/big-data. Accessed on: 13 Oct. 2020.
“Cellular operators know everything about their subscribers”, Vedomosti. Accessed on: 13 Oct. 2020. [Online]. Available: https://www.vedomosti.ru/technology/ articles/2015/05/26/593579 -sotovie-operatori-znayut-vse-o-svoih-abonentah
L. Globa and N. Gvozdetska, “Comprehensive Energy Efficient Approach to Workload Processing in Distributed Computing Environment”, 2020 IEEE International Black Sea Conference on Communications and Networking (BlackSeaCom), Odessa, Ukraine, 2020, pp. 1–6. doi: 10.1109/BlackSeaCom48709.2020.9235010.