The symmetry between customer expectations and operator goals, on one hand, and the digital transition of the railways, on the other hand, is one of the main factors affecting green transport sustainability. The European Train Control System (ETCS) was created to improve interoperability between different railway signaling systems and increase safety and security. While there are a lot of ETCS Level 2 deployments all over the world, the specifications of ETCS Level 3 are under development. ETCS Level 3 is expected to have a significant impact on automatic train operation, protection, and supervision. In this paper, we present an innovative control system architecture that allows the incorporation of artificial intelligence (AI)/machine learning (ML) applications. The architecture features control function virtualization and programmability. The concept of an intelligent railway controller (IRC) is introduced as being a piece of cloud software responsible for the control and optimization of railway operations. A microservices-based approach to designing the IRC’s functionality is presented. The approach was formally verified, and some of its performance metrics were identified.

The cloudification and virtualisation of railway functions have the potential to improve railway operation efficiency, reliability, safety, and security, as well as to enhance passenger experience by offering innovative services. This paper considers issues related to the management and orchestration of railway clouds that host cloudified railway functions. A microservices-based approach to the design of railway cloud management and orchestration functionality is proposed. The basic railway cloud concepts were defined, and functionality related to the basic orchestration of the railway cloud and deployments is analysed in order to derive the requirements of platform resources and workload management. This functionality is further designed in the form of microservices, meaning that they could possibly be used in orchestration applications to enable improvements in scalability, fault isolation, and data security. The design of microservices follows the principles of the Representational State of Transfer (REST) application programming interface (API) as a set of interlinked resources. Resources related to railway cloud orchestration are identified with their associated data, relationships to other resources, and applicable methods. The resources’ methods are used in railway applications to implement the required orchestration functionality and to maintain the state of railway cloud orchestration processes. To verify the synthesised microservices, the common orchestration application logic and microservices’ logic were modelled, and it was proved that the orchestration processes, which run concurrently, expose equivalent behaviour. The proposed approach was validated using a simulation, aiming to evaluate injected latency as a key performance indicator for the reliability and safety of railway operations. Additionally, some safety and security issues related to railway cloud management and orchestration are considered.

The increasing number of connected devices which use Internet of Things (IoT) technology and variety of associated services is a real challenge to interoperability. There is a need of an abstraction layer which hides the technology heterogeneity. The paper presents an approach to data modeling in the domain of home energy saving which extends existing solutions with context-ware concepts and relationships. Requirements to data annotation are identified by use cases. Problem-solving principle is applied to data annotation which defines the vocabulary related to a certain task or activities. An observation and actuation models which show how data annotation works are proposed and formally verified. As a proof of concept, the server model includes web services that illustrate the usage of the proposed data annotation. The potential of home appliance power control is estimated.

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.

The virtualization and automation of network functions will be key features of future high-speed railway networks, which have to provide dependable, safe, and secure services. The virtualization of railway network functions will enable functions such as train control, train integrity protection, shunting control, and trackside monitoring and maintenance to be virtualized and to be run on general-purpose hardware. Network function virtualization combined with edge computing can deliver dynamic, low-latency, and reliable services. The automation of railway operations can be achieved by embedding intelligence into the network to optimize the railway operation performance and to enhance the passenger experience. This paper presents an innovative railway network architecture that features distributed intelligence, function cloudification and virtualization, openness, and programmability. The focus is on time-tolerant and time-sensitive intelligent services designed to follow the principles of service-oriented architecture. The interaction between identified logical identities is illustrated by use cases. The paper provides some details of the design of the interface between distributed intelligent services and presents the results of an emulation of the interface performance.