5G systems promise to enable autonomous vehicles by empowering road-, water-, and air-vehicles with ultra low latency communications and computing at edge in order to share and process data from multiple sensors. However, in order to realize such fully Connected and Automated Mobility (CAM) for cars, drones and vessels, a crucial intermediary step must be fully achieved: 5G-based tele-operated transport. In order to do so, the European project H2020 5G-Blueprint aims to design, test, and validate in real deployments a 5G-enabled tele-operated transport and its enabling functions in both a relevant and operational environment realised through cross-border trials on the road and on the water along 5G corridors in the Dutch and Belgian border area, resulting in a blueprint for future cooperation on 5G-enabled CAM between public, private and semi-private parties (e.g, ports), gaining new and innovative insights on the stringent particular requirements for safe CAM, on the architecture, on governance and relevant business models.

As Cooperative Intelligent Transportation Systems (C-ITS) hold many promises in reducing societal costs of traffic, the European Commission aspires to move to more C-ITS deployments in the coming years. Despite the promise of socioeconomic benefits, C-ITS deployments require substantial investments from European Member States in roadside infrastructure and in central traffic management systems. These investment costs currently outweigh the expected benefits, due to limited expected uptake of C-ITS in European passenger cars. However, since traffic volumes and the associated societal costs are not uniformly distributed along highways, investments in specific Road-Side Units (RSUs) locations might be viable, despite an overall RSU investment appraisal seeming unfeasible. Therefore, in this work, a greedy techno-economic selection algorithm for RSU deployment locations is presented. It was found that, for Flanders, a subset of potential RSU locations resulted in a positive business case from societal point of view, whereas the initial overall investment case resulted in a negative assessment conclusion.

Base station sharing is currently considered one of the most promising solutions for reducing the energy consumption costs of cellular networks. This paper presents a game theoretic framework for the study of such cooperative solutions where different mobile network operators (MNOs) decide to switch off subsets of their base stations during off-peak hours and roam their traffic to the remaining stations. The solution is based on a detailed optimization framework that determines exactly which base stations should remain active and how much traffic each one of them should serve, so as to maximize the aggregate energy savings. Accordingly, using the axiomatic Shapley value rule, it is determined how the benefits from the cooperation, i.e., the cost savings, should be dispersed among the cooperating MNOs. It is proved that this coalitional game with transferrable utilities has a nonempty core, and thus there exists a cooperation solution that incentivizes the participation of all operators. Moreover, using a thorough numerical analysis, it is shown that the benefits achieved with the implementation of the cooperation strategy depend mainly on the power consumption characteristics of the MNOs, which in turn are related to the number, type, and technology of their base stations. Overall, the energy savings are found to be most sensitive to the technology of the used base stations, and more precisely to the no-load base station energy consumption which defines the energy waste in a network.

eHealth, mHealth and eCare services are growing in numbers at a fast pace. This is mainly driven by technology and the societal challenges of an aging and more chronically burdened population while pressure on both human and financial resources increases. Though the adoption of these digital health services is challenging and experience difficulties. This work focusses on the main barriers that cause a `gap' in the value network. Via case research following barriers are identified: 1) low willingness to pay, 2) unbalanced cost/benefit ratios of the actors or unfair cost allocation and 3) negative impacted business models. Furthermore the several roles of the government within the value network of digital health services are discussed and reflections and guidelines for digital health service developers are foreseen.

Current nurse call systems hinder the efficiency of nurses as the systems are not aware of the type of requested help and the context in which their help is required. To tackle these issues, we have developed an ontology-based nurse call system that automatically takes the patients' and caregivers' profiles and context into account when assigning calls to nurses by modelling this information in an ontology, i.e., a formal domain model. For example, current tasks of the nurses and trust relationship with patients are considered while allocating calls to caregivers. Focus is not only on creating a higher quality patient care, but also on distributing the workload more evenly over all caregivers. However, not in all hospital departments such a smart nurse call system will have a significant impact, e.g., geriatric versus emergency care. To gain insights into the total impact of a smart nurse call system, a dedicated discrete event simulation (DES) model is presented that tests its performance. Based on realistic nurse call logs and information gathered at representative hospital departments through interviews and observations, the simulation model allows optimizing decisions, modelled as rules based on the information captured in the ontology, to allocate calls to the best suited nurse. Several scenarios with a varying number of calls, staff members, etc. are tested to be able to define the effectiveness and the (dis)advantages of the ontology-based system with respect to the current one. In conclusion, recommendations are made towards improving the currently employed nurse call systems in hospitals.

The healthcare sector is an incredibly complex system with many public and private actors and a wide diversity of services. Because of the aging society and the growing evolution of health expenditures, pressure on available resources (time, people, budget, etc.) is increasing. Innovative ICT supported eCare and eCure services are expected to increase efficiency, coordination and organization of care. Currently many initiatives already introduced ICT-supported eCare services into the current healthcare ecosystem. However, it's quite a challenge to estimate the impact and expected uptake of these new eCare services. It's no surprise that only few services commercially succeeded. This paper presents a methodology that identifies and evaluates the PEST factors (political, economical, social and technological aspects) that impact the involved care actors when introducing eCare services. The model takes into account the overall socio-economic aspects of the service, but also the subjective importance that an individual actor can ascribe to a particular eCare service. Combining the impact of these PEST factors leads to an expected adoption rate. Both new services and existing initiatives can be compared to one another and the impact of economies of scale can be investigated. In case a negative impact on some actors is observed, the model proposes cost allocation or service offer alternatives to ameliorate the business case for a particular service. Finally, a sensitivity analysis helps to indicate the most significant parameters that drive the business case.

Nowadays, many telecom operators are reluctant to roll out a new fiber to the home (FTTH) infrastructure, as they are put off by the high investment costs. Inspired by several local FTTH initiatives, especially in Western Europe, this paper considers an FTTH rollout by a local community. We show that clearly different economics play a part in case a community would roll out the FTTH infrastructure, and we give also an indication of some required conditions to obtain a feasible FTTH rollout. To get realistic results, the techno-economic study has been applied on a municipality network in the city of Ghent, located in Belgium. We have performed a cost/benefit analysis, and different rollout schemes are compared to each other. As the introduction of a new technology involves a lot of uncertainties, it is of great importance to determine the most influencing parameters. For that purpose, we have executed a detailed sensitivity analysis, which also provide us with a general forecast of the outcome of the considered case study.

Generalized Multi-Protocol Label Switching (GMPLS) has become the protocol suite of choice for unified control plane implementation. However, its adoption is facing major challenges in terms of feasibility, performance, and gain when migrating from legacy packet over optical multi-layer networks driven by overlaid control planes. The ITEA TBONES project aims at tackling both objectives through the development of a platform including all the elements constituting such networks: network dimensioning, management plane and GMPLS control plane. This paper details the control plane architecture of the TBONES software platform, including its realization and applicability for multi-area networks, as well as the Testbed. Several experiments are described, both for validation and for demonstration of its capabilities and future usage.

Today, the Belgian research network GIGANET, managed by BELNET, consists of two star-shaped structures, centralized in Brussels, from where data transmission lines depart to national PoPs (point-of-presence), which are located all over the country. Local universities, colleges and other research institutions connect to their nearest PoP. Current capacity is way below predictions for the near future, thus the network needs to be scaled up dramatically. Also, there is a new demand for securely connecting distant institutions, due to several associations between them. We studied the optimal design of the future next-generation network GIGANET2, choosing a new topology, predicting future capacity demands and taking into account real pricing information obtained from telecom companies and optical hardware vendors. The study consisted of involved optimization efforts, and large-scale comparisons of optical hardware and available fiber infrastructure. This work resulted in the design of a physical optical ring topology, together with three network scenarios which are subject to different bandwidth, reliability and cost considerations, closely matching the institutions' requirements. This paper presents the final results of the study.