The increased use of smart Electric Vehicles (EVs) and Plug-in Electric Vehicles (PEV) opened a new area of research and development. The number of EV charging sites has considerably increased in residential as well as in public areas. Within these EV charging sites, various entities need to communicate in a secure and efficient way. The Open Charge Point Protocol (OCPP) offers a way to coordinate this communication and is already being used in many implementations. However, only the latest OCPP 2.0 version of the protocol includes certain security features. In this article, we present the entities that take part in an OCPP-based smart charging scenario, we identify security issues and threats and present solutions that have been proposed by scholars. We identify open security issues for OCPP and propose future research directions for the security enhancement of the protocol.

Communication networks for healthcare environments support various application types and should be capable of providing them with the required Quality of Service (QoS) in terms of reliable data delivery, considerable data rate and low latency. The introduction of Tactile Internet (TI) healthcare applications is expected to upgrade the level of provided services to patients. The requirements of these applications are very stringent and a major requirement is that the existing network infrastructure must support them. Passive Optical Networks (PONs) have been proposed as an ideal candidate to support such demanding environments. One of the major challenges of such networks, which significantly affects the provided QoS, is the effective resource allocation in both the time and the wavelength domains. The existing resource allocation algorithms for PONs were designed without considering the stringent requirements of TI applications thus making PON support for TI inefficient. In this paper, a new double per priority queue dynamic wavelength and bandwidth allocation algorithm is presented. This algorithm allocates the network resources efficiently and fairly using several techniques, in order to meet the QoS demands of Tactile and other types of healthcare applications. Extensive simulation results indicate the effectiveness of the proposed algorithm to provide the required QoS for medical applications under various simulation scenarios whereas other well-known schemes are shown to lack such support.

The intelligent transportation services are part of the urban planning and smart <;everything> concept which aims to improve the user experience and to deliver new ways with increased added value. To prototype these services or to enhance the legacy transportation services with the evolving technology, it is likely to create significant overheads during various phases of the service lifecycle, such as during the design phase. To effectively tackle the challenges that appear in such an endeavour, the selection of the optimal modelling method and of the appropriate language plays a crucial role in creating and enabling innovative and efficient transportation service operations. In this paper, the utilization of a business-oriented modelling approach is proposed for the modelling of the Decision Support System (DSS) that supports these services. Two scenarios are assessed considering the DSS behaviour of an IoT-based intelligent transportation service. Finally, this paper provides a discussion on the modelling method in regard to the DSS processes and how this method can be widely utilised for developing novel intelligent transportation services.

Within the Internet of Things (IoT) ecosystem, there is a need to interconnect networks of sensors and smart objects in a way that they can intelligently interact with humans. In most cases, these networks have been implemented following the machine-to-machine (M2M) communication disciplines. To adequately design such an emerging system which also has legacy technology characteristics, it is crucial to adopt an architecture reference model. In the context of this work, an architecture and characteristics assessment is conducted to form a roadmap of evolution from an M2M solution to an IoT in the field of Autonomous Vehicles (AVs). Then, an architecture for an AV prototype within the IoT ecosystem is proposed; the intelligent Bus on Campus (iBuC). The respective services are illustrated through a customised real-life scenario.