Autors: Atanasov, I. I., Dimitrova D., Pencheva E., Trifonov V.
Title: Railway Cloud Resource Management as a Service
Keywords: cloud computing, cloud management, formal verification, railways, RESTful services, service-based architecture, state models

Abstract: Cloud computing has the potential to accelerate the digital journey of railways. Railway systems are big and complex, involving a lot of parts, like trains, tracks, signaling systems, and control systems, among others. The application of cloud computing technologies in the railway industry has the potential to enhance operational efficiency, data management, and overall system performance. Cloud management is essential for complex systems, and the automation of management services can speed up the provisioning, deployment, and maintenance of cloud infrastructure and applications by enabling visibility across the environment. It can provide consistent and unified management over resource allocation, streamline security processes, and automate the monitoring of key performance indicators. Key railway cloud management challenges include the lack of open interfaces and standardization, which are related to the vendor lock-in problem. In this paper, we propose an approach to design the railway cloud resource management as a service. Based on typical use cases, the requirements to fault and performance management of the railway cloud resources are identified. The main functionality is designed as RESTful services. The approach feasibility is proved by formal verification of the cloud resource management models supported by cloud management application and services. The proposed approach is open, in contrast to any proprietary solutions and feature scalability and interoperability.

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Issue

Future Internet, vol. 17, 2025, Albania, https://doi.org/10.3390/fi17050192

Цитирания (Citation/s):
1. Stefan I.-L., Mateescu A., Lentoiu I., Raileanu S., Anton F.D., Popescu D.C., Sacala I.S., Implementation and Performance Analysis of an Industrial Robot’s Vision System Based on Cloud Vision Services, 2025, Future Internet, issue 5, vol. 17, DOI 10.3390/fi17050200, eissn 19995903 - 2025 - в издания, индексирани в Scopus
2. Stefan, IL, Mateescu, A, Lentoiu, I, Raileanu, S, Anton, FD, Popescu, DC, Sacala, IS, Implementation and Performance Analysis of an Industrial Robot's Vision System Based on Cloud Vision Services, FUTURE INTERNET, vol 17, 2025, issn: 1999-5903, art_no: ARTN 200, doi: 10.3390/fi17050200 - 2025 - в издания, индексирани в Web of Science
3. Atanasov, I, Pencheva, E, Nikolova, K, Management of Virtualized Railway Applications, INFORMATION, vol 16, 2025, eissn: 2078-2489, art_no: ARTN 712, doi: 10.3390/info16080712 - 2025 - в издания, индексирани в Scopus и/или Web of Science

Вид: статия в списание, публикация в издание с импакт фактор, публикация в реферирано издание, индексирана в Scopus и Web of Science