Hybrid Simulation and Test of Vessel Traffic Systems on the Cloud

This paper presents a cloud-based hybrid simulation platform to test large-scale distributed System-of-Systems (SoS) for the management and control of maritime traffic, the so-called Vessel Traffic Systems (VTS). A VTS consists of multiple, heterogeneous, distributed and interoperating systems, including radar, automatic identification systems, direction finders, electro-optical sensors, gateways to external VTSs, information systems; identifying, representing and analyzing interactions is a challenge to the evaluation of the real risks for safety and security of the marine environment. The need for reproducing in fabric the system behaviors that could occur in situ demands for the ability of integrating emulated and simulated environments to cope with the different testability requirements of involved systems and to keep testing cost sustainable. The platform exploits hybrid simulation and virtualization technologies, and it is deployable on a private cloud, reducing the cost of setting up realistic and effective testing scenarios

A Review on Vehicle Classification and Potential Use of Smart Vehicle-Assisted Techniques

Vehicle classification (VC) is an underlying approach in an intelligent transportation system and is widely used in various applications like the monitoring of traffic flow, automated parking systems, and security enforcement. The existing VC methods generally have a local nature and can classify the vehicles if the target vehicle passes through fixed sensors, passes through the short-range coverage monitoring area, or a hybrid of these methods. Using global positioning system (GPS) can provide reliable global information regarding kinematic characteristics; however, the methods lack information about the physical parameter of vehicles. Furthermore, in the available studies, smartphone or portable GPS apparatuses are used as the source of the extraction vehicle’s kinematic characteristics, which are not dependable for the tracking and classification of vehicles in real time. To deal with the limitation of the available VC methods, potential global methods to identify physical and kinematic characteristics in real time states are investigated. Vehicular Ad Hoc Networks (VANETs) are networks of intelligent interconnected vehicles that can provide traffic parameters such as type, velocity, direction, and position of each vehicle in a real time manner. In this study, VANETs are introduced for VC and their capabilities, which can be used for the above purpose, are presented from the available literature. To the best of the authors’ knowledge, this is the first study that introduces VANETs for VC purposes. Finally, a comparison is conducted that shows that VANETs outperform the conventional techniques

A Review on Vehicle Classification and Potential Use of Smart Vehicle-Assisted Techniques

Vehicle classification (VC) is an underlying approach in an intelligent transportation system and is widely used in various applications like the monitoring of traffic flow, automated parking systems, and security enforcement. The existing VC methods generally have a local nature and can classify the vehicles if the target vehicle passes through fixed sensors, passes through the short-range coverage monitoring area, or a hybrid of these methods. Using global positioning system (GPS) can provide reliable global information regarding kinematic characteristics; however, the methods lack information about the physical parameter of vehicles. Furthermore, in the available studies, smartphone or portable GPS apparatuses are used as the source of the extraction vehicle’s kinematic characteristics, which are not dependable for the tracking and classification of vehicles in real time. To deal with the limitation of the available VC methods, potential global methods to identify physical and kinematic characteristics in real time states are investigated. Vehicular Ad Hoc Networks (VANETs) are networks of intelligent interconnected vehicles that can provide traffic parameters such as type, velocity, direction, and position of each vehicle in a real time manner. In this study, VANETs are introduced for VC and their capabilities, which can be used for the above purpose, are presented from the available literature. To the best of the authors’ knowledge, this is the first study that introduces VANETs for VC purposes. Finally, a comparison is conducted that shows that VANETs outperform the conventional techniques

Service-based Fault Tolerance for Cyber-Physical Systems: A Systems Engineering Approach

Cyber-physical systems (CPSs) comprise networked computing units that monitor and control physical processes in feedback loops. CPSs have potential to change the ways people and computers interact with the physical world by enabling new ways to control and optimize systems through improved connectivity and computing capabilities. Compared to classical control theory, these systems involve greater unpredictability which may affect the stability and dynamics of the physical subsystems. Further uncertainty is introduced by the dynamic and open computing environments with rapidly changing connections and system configurations. However, due to interactions with the physical world, the dependable operation and tolerance of failures in both cyber and physical components are essential requirements for these systems.The problem of achieving dependable operations for open and networked control systems is approached using a systems engineering process to gain an understanding of the problem domain, since fault tolerance cannot be solved only as a software problem due to the nature of CPSs, which includes close coordination among hardware, software and physical objects. The research methodology consists of developing a concept design, implementing prototypes, and empirically testing the prototypes. Even though modularity has been acknowledged as a key element of fault tolerance, the fault tolerance of highly modular service-oriented architectures (SOAs) has been sparsely researched, especially in distributed real-time systems. This thesis proposes and implements an approach based on using loosely coupled real-time SOA to implement fault tolerance for a teleoperation system.Based on empirical experiments, modularity on a service level can be used to support fault tolerance (i.e., the isolation and recovery of faults). Fault recovery can be achieved for certain categories of faults (i.e., non-deterministic and aging-related) based on loose coupling and diverse operation modes. The proposed architecture also supports the straightforward integration of fault tolerance patterns, such as FAIL-SAFE, HEARTBEAT, ESCALATION and SERVICE MANAGER, which are used in the prototype systems to support dependability requirements. For service failures, systems rely on fail-safe behaviours, diverse modes of operation and fault escalation to backup services. Instead of using time-bounded reconfiguration, services operate in best-effort capabilities, providing resilience for the system. This enables, for example, on-the-fly service changes, smooth recoveries from service failures and adaptations to new computing environments, which are essential requirements for CPSs.The results are combined into a systems engineering approach to dependability, which includes an analysis of the role of safety-critical requirements for control system software architecture design, architectural design, a dependability-case development approach for CPSs and domain-specific fault taxonomies, which support dependability case development and system reliability analyses. Other contributions of this work include three new patterns for fault tolerance in CPSs: DATA-CENTRIC ARCHITECTURE, LET IT CRASH and SERVICE MANAGER. These are presented together with a pattern language that shows how they relate to other patterns available for the domain

Next Generation Internet of Things – Distributed Intelligence at the Edge and Human-Machine Interactions

This book provides an overview of the next generation Internet of Things (IoT), ranging from research, innovation, development priorities, to enabling technologies in a global context. It is intended as a standalone in a series covering the activities of the Internet of Things European Research Cluster (IERC), including research, technological innovation, validation, and deployment.The following chapters build on the ideas put forward by the European Research Cluster, the IoT European Platform Initiative (IoT–EPI), the IoT European Large-Scale Pilots Programme and the IoT European Security and Privacy Projects, presenting global views and state-of-the-art results regarding the next generation of IoT research, innovation, development, and deployment.The IoT and Industrial Internet of Things (IIoT) are evolving towards the next generation of Tactile IoT/IIoT, bringing together hyperconnectivity (5G and beyond), edge computing, Distributed Ledger Technologies (DLTs), virtual/ andaugmented reality (VR/AR), and artificial intelligence (AI) transformation.Following the wider adoption of consumer IoT, the next generation of IoT/IIoT innovation for business is driven by industries, addressing interoperability issues and providing new end-to-end security solutions to face continuous treats.The advances of AI technology in vision, speech recognition, natural language processing and dialog are enabling the development of end-to-end intelligent systems encapsulating multiple technologies, delivering services in real-time using limited resources. These developments are focusing on designing and delivering embedded and hierarchical AI solutions in IoT/IIoT, edge computing, using distributed architectures, DLTs platforms and distributed end-to-end security, which provide real-time decisions using less data and computational resources, while accessing each type of resource in a way that enhances the accuracy and performance of models in the various IoT/IIoT applications.The convergence and combination of IoT, AI and other related technologies to derive insights, decisions and revenue from sensor data provide new business models and sources of monetization. Meanwhile, scalable, IoT-enabled applications have become part of larger business objectives, enabling digital transformation with a focus on new services and applications.Serving the next generation of Tactile IoT/IIoT real-time use cases over 5G and Network Slicing technology is essential for consumer and industrial applications and support reducing operational costs, increasing efficiency and leveraging additional capabilities for real-time autonomous systems.New IoT distributed architectures, combined with system-level architectures for edge/fog computing, are evolving IoT platforms, including AI and DLTs, with embedded intelligence into the hyperconnectivity infrastructure.The next generation of IoT/IIoT technologies are highly transformational, enabling innovation at scale, and autonomous decision-making in various application domains such as healthcare, smart homes, smart buildings, smart cities, energy, agriculture, transportation and autonomous vehicles, the military, logistics and supply chain, retail and wholesale, manufacturing, mining and oil and gas