Smart cities solutions are often monolithically implemented, from sensors data handling through to the provided services. The same challenges are regularly faced by different developers, for every new solution in a new city. Expertise and know-how can be re-used and the effort shared. In this article we present the methodologies to minimize the efforts of implementing new smart city solutions and maximizing the sharing of components. The final target is to have a live technical community of smart city application developers. The results of this activity comes from the implementation of 35 city services in 27 cities between Europe and South Korea. To share efforts, we encourage developers to devise applications using a modular approach. Single-function components that are re-usable by other city services are packaged and published as standalone components, named Atomic Services. We identify 15 atomic services addressing smart city challenges in data analytics, data evaluation, data integration, data validation, and visualization. 38 instances of the atomic services are already operational in several smart city services. We detail in this article, as atomic service examples, some data predictor components. Furthermore, we describe real-world atomic services usage in the scenarios of Santander and three Danish cities. The resulting atomic services also generate a side market for smart city solutions, allowing expertise and know-how to be re-used by different stakeholders.

In recent years, the evolution of urban environments, jointly with the progress of the Information and Communication sector, have enabled the rapid adoption of new solutions that contribute to the growth in popularity of Smart Cities. Currently, the majority of the world population lives in cities encouraging different stakeholders within these innovative ecosystems to seek new solutions guaranteeing the sustainability and efficiency of such complex environments. In this work, it is discussed how the experimentation with IoT technologies and other data sources form the cities can be utilized to co-create in the OrganiCity project, where key actors like citizens, researchers and other stakeholders shape smart city services and applications in a collaborative fashion. Furthermore, a novel architecture is proposed that enables this organic growth of the future cities, facilitating the experimentation that tailors the adoption of new technologies and services for a better quality of life, as well as agile and dynamic mechanisms for managing cities. In this work, the different components and enablers of the OrganiCity platform are presented and discussed in detail and include, among others, a portal to manage the experiment life cycle, an Urban Data Observatory to explore data assets, and an annotations component to indicate quality of data, with a particular focus on the city-scale opportunistic data collection service operating as an alternative to traditional communications.

Low Earth Orbit (LEO) satellite constellations are envisioned as a complementary or integrated part of 5G and future 6G networks for broadband or massive access, given their capabilities of full Earth coverage in inaccessible or very isolated environments. Although the queuing and end-to-end delays of such networks have been analyzed for channels with fixed statistics, currently there is a lack in understanding the effects of more realistic time-varying channels for traffic aggregation across such networks. Therefore, in this work we propose a queuing model for LEO constellation-based networks that captures the inherent variability of realistic satellite channels, where ground-to-satellite/satellite-to-ground links may present extremely poor connection periods due to the Land Mobile Satellite (LMS) channel. We verify the validity of our model with an extensive event-driven simulator framework analysis capturing the characteristics of the considered scenario. We later study the queuing and end-to-end delay distributions under such channels with various link, traffic, packet and background conditions, while observing good match between theory and simulation. Our results show that ground-to-satellite/satellite-to-ground links and background traffic have a much stronger impact over the end-to-end delay in mean and particularly variance, even with moderate queues, than unobstructed inter-satellite connections in outer space on an established path between two ground stations and through the constellation. This might hinder the usability of these networks for services with stringent time requirements.

The QUIC protocol, which was originally proposed by Google, has recently gained a remarkable presence. Although it has been shown to outperform TCP over a wide range of scenarios, there exist some doubts on whether it might be an appropriate transport protocol for IoT. In this paper, we specifically tackle this question, by means of an evaluation carried out over a real platform. In particular, we conduct a thorough characterization of the performance of the MQTT protocol, when used over TCP and QUIC. We deploy a real testbed, using commercial off-the-shelf devices, and we analyze two of the most important key performance indicators for IoT: delay and energy consumption. The results evince that QUIC does not only yield a notable decrease in the delay and its variability, over various wireless technologies and channel conditions, but it does not hinder the energy consumption.

This work tackles the problem faced by network/ infrastructure providers of jointly selecting routing and functional split level to satisfy requests from virtual mobile network operators (vMNOs). We build a novel system model that brings together all the involved elements and features, embracing split levels defined by the 3GPP and packet switch fronthaul network. To our best knowledge, this is the first work that provides a solution for multiple vMNO requests considering the two aforementioned sub-problems (i.e. split selection and routing). We use the model defined to formulate an optimization problem, which is characterized by the exponential size of its search space. We propose two heuristic approaches to address this problem: (1) a greedy scheme, and (2) an evolutionary algorithm, which is also improved with a specialized initialization. We conduct extensive experiments to assess the performance and behavior of the proposed methods, over varying network instances. When possible, we also perform comparisons with respect to the optimal solution and a well-known commercial solver. Our results indicate that the proposed techniques represent appropriate trade-offs between solution quality and execution time, and can serve complementary goals: the quality of the results yielded by our evolutionary method are better, but at the cost of longer execution times; in contrast, our greedy algorithm offers a reasonably appropriate performance, with an execution time that is notably lower. Our experiments show that it is possible to produce near-optimal results to the above complex problem through computationally efficient algorithmic solutions.

We study the delay over virtual RAN (vRAN) topologies, entailing base stations that are divided into centralized and distributed units, as well as the packet-switched fronthaul network that connects them. We consider the use of flexible functional split, where the functions that are executed at each of these two entities can be dynamically shifted. We propose a queuing-based model, which is able to precisely mimic the behavior of such nodes, and we validate it by means of extensive simulations. We also exploit Jackson Networks theory to establish the end-to-end delay over the fronthaul network, allowing us to assess the impact of having different networking policies and conditions (for instance, background traffic or heterogeneous technologies). Thanks to the simulator we can also broaden the analysis, by studying the delay variability. In addition, we conduct an in-depth analysis of the performance exhibited by a realistic network setup, whose particular characteristics might hinder the services performance, due to the longer dwell times at each split configuration. The results evince the validity of the proposed model, even under realistic conditions. We show that it might not be enough to guarantee an average stable operation of the centralized/distributed units, but the traffic load should remain below the slowest service rate, to avoid reaching unacceptable delays. An increase of $> 100 \times $ is observed in the delay, using the realistic network setup, when these conditions do not hold.