# Railway Cloud: Management and Orchestration Functionality Designed as Microservices
## 2 Related Works  
Research related to railways' cloudification can be classified into three areas: the employment of edge clouds related to the optimisation of offloading real-time control onto edge clouds; cloud computing platform's architectures concerning resilient and secured frameworks embedding intelligent workflows and virtualisation technologies; and cloud-based railway applications for automatic train supervision, track monitoring and surveillance, fault diagnostics, and ticketing systems. Real-time monitoring in railways provides accurate support in terms of fault management, enabling the generation of valuable and actionable insights, and edge computing is a good method used to perform analytics close to data sources. In [26], the authors propose a method for train predictive control, which offloads computations related to real-time control onto edge services, while a deep learning-based algorithm for trajectory prediction is executed on a centralised server. In [27], an approach to optimise railway logistics based on mobile edge cloud is proposed. The authors of [28] exploit the benefits of multi-access edge computing to offload train tasks to edge servers using blockchain technology for authenticity. An edge computing-based solution for the problem of the processing of mass data, gathered from intelligent railway station equipment, is presented in [29]. Moving the tasks of railway operation and maintenance to the cloud sets strict requirements in terms of reliability, safety, and security. The resilience requirements of the cloud for its use in critical railway systems are considered in [30]. The capabilities of the cloud to deploy virtualised real-time, safety-critical functions to commercial off-the-shelf products are studied in [31]. To cope with problems related to diverse logistic information across borders, in [32], the authors propose a hybrid cloud with three layers of services. A cloud-based architecture of an intelligent operation and maintenance system in railways is presented in [33], with focus on the respective workflows. In [34], the authors study the capabilities of building cloud computing platforms for railways with open-source products and propose a high-level security architecture for the cloud. In [35], the authors present the idea of cloud-based supervisory control systems for urban railway transport and identify the related functionality, which could be synthesised as microservices. However, the authors do not provide any details on the design of microservices and do not discuss cloud management aspects. A study on security architectures and key technologies for railway clouds is provided in [36]. Most of the existing research focused on railway clouds is devoted to specific cloud-based railways applications [37]. These applications cover automatic train supervision [38], virtual coupling [39], track surveillance and monitoring [40; 41], fault detection in railway infrastructure components [42], predictive maintenance [43], smart ticketing systems [44; 45], train movements prediction [46], operation and maintenance of rail power supply systems [47], and security-related issues [48; 49]. Table 1 summarizes some of the recent works concerning problems related to the aspects of the railway cloud. The management of industrial clouds comes with a set of problems related to data security and privacy, performance and reliability, cloud migration, interoperability, optimization of management costs, and required skills and knowledge.