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A common concern in smart cities is the focus on sensing procedures to provide city-wide information to city managers and citizens. To meet the growing demands of smart cities, the network must provide the ability to handle a large number of mobile sensors/devices, with high heterogeneity and unpredictable mobility, by collecting and delivering the sensed information for future treatment. This work proposes a multi-wireless technology communication platform for opportunistic data gathering and data exchange with respect to smart cities. Through the implementation of a proprietary long-range (LoRa) network and an urban sensor network, our platform addresses the heterogeneity of Internet of Things (IoT) devices while conferring communications in an opportunistic manner, increasing the interoperability of our platform. It implements and evaluates a medium access communication (MAC) protocol for LoRa networks with multiple gateways. It also implements mobile Opportunistic VEhicular (mOVE), a delay-tolerant network (DTN)-based architecture to address the mobility dimension. The platform provides vehicle-to-everything (V2X) communication with support for highly reliable and actionable information flows. Moreover, taking into account the high mobility pattern that a smart city scenario presents, we propose and evaluate two forwarding strategies for the opportunistic sensor network.

Advanced communication networks, such as 5G and beyond, will be a complex ecosystem made of multiple physically interconnected elements, implying that the upcoming network will have to address capabilities such as flexibility, programmability and extensibility. This article, describes an Open and Extensible 5G Network Function Virtualisation (NFV) based Reference ecosystem of experimental facilities, named 5GinFIRE, that integrates existing facilities with new vertical-specific ones but also lays down the foundations for instantiation fully softwarised architectures of vertical industries and experimenting with them. Additionally, we present 5GinFIRE as the forerunner experimental playground, together with three uses cases, wherein new components, architecture designs and APIs may be tried and proposed before they are ported to more industrially mainstream 5G networks that are expected to emerge in large scale.

In this paper, we consider a high-speed highway mobility scenario, where the available knowledge about the network's topology is used to improve the routing path duration. The improvement is mainly due to the use of a topology control algorithm, which increases the path duration by decreasing the probability of path breaks. For network regions having an enough density of vehicles, the packets are preferentially routed over the oldest links created by the vehicles moving in the same direction. For smaller values of vehicles' density, the routing preferentially uses the most recent links created in both moving directions. This choice is shown to increase the routing path duration.The topology control scheme here proposed can be easily integrated in the existing routing protocols: we describe how to integrate it in the Optimized Link-State Routing Protocol (OLSR).1 We compare the performance of our approach with other routing protocols for different values of vehicles' density. The comparison includes end-to-end path delay, path availability and path length (in number of hops). Finally, we evaluate the path duration achieved with our approach, concluding that it exhibits a significant improvement over the most relevant topology and position-based routing protocols. KeywordsTopology control Routing protocols Vehicular ad hoc networks

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This paper studies the service time required to transmit a packet in an opportunistic spectrum access scenario, where an unlicensed secondary user (SU) transmits a packet using the radio spectrum licensed to a primary user (PU). Considering a cognitive radio network, it is assumed that during the transmission period of an SU multiple interruptions from PUs may occur, increasing the time needed to transmit a packet. Assuming that the SU's packet length follows a geometric distribution, we start by deriving the probability of an SU transmitting its packet when k > 0 periods of PU's inactivity are observed. As the main contribution of this paper, we derive the characteristic function of the service time, which is further used to approximate its distribution in a real-time estimation process. The proposed methodology is independent of the SUs' traffic condition, i.e., both saturated or non-saturated SU's traffic regime is assumed. Our analysis provides a lower bound for the service time of the SUs, which is useful to determine the maximum throughput achievable by the secondary network. Simulation results are used to validate the analysis, which confirm the accuracy of the proposed methodology.

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