Driven by the increasing number of connected vehicles and related services, powerful communication and computation capabilities are needed for vehicular communications, especially for real-time and safety-related applications. Cellular network consists of radio access technologies including the current long term evolution (LTE), the LTE Advanced, and the forthcoming 5th Generation mobile communication systems (5G). It covers large areas and has the ability to provide high data rate and low latency communication services to mobile users. It is considered as the most promising access technology to support real-time vehicular communications. Meanwhile, fog is an emerging architecture for computing, storage, and networking, in which fog nodes can be deployed at base stations to deliver cloud services close to vehicular users. In fog computing enabled cellular networks, mobility is one of the most critical challenges for vehicular communications to maintain the service continuity and to satisfy the stringent service requirements, especially when the computing and storage resources are limited at the fog nodes. Service migration, relocating services from one fog server to another in a dynamic manner, has been proposed as an effective solution to the mobility problem. To support service migration, both computation and communication techniques need to be considered. Given the importance of protocol design to support mobility of the vehicles and maintain high network performance, in this article, we investigate the service migration in the fog computing enabled cellular networks. We propose a Quality of Service (QoS) aware scheme based on the existing handover procedures to support the real-time vehicular services. A case study based on a realistic vehicle mobility pattern for Luxembourg scenario is carried out, where the proposed scheme as well as the benchmarks are compared by analyzing latency and reliability as well as migration cost.

A fundamental and computationally challenging optimization task in wireless networks is to maximize the number of simultaneous transmissions, subject to signal-to-noise-and-interference ratio (SINR) requirements at the receivers. The conventional approach guaranteeing global optimality is to solve an integer programming model with explicit SINR constraints. These constraints are however numerically very difficult. We develop a new integer programming algorithm based on a much more effective representation of the SINR constraints. Computational experiments demonstrate that the new approach performs significantly better in proving optimality.

With the emerging connected automated vehicles, 5G and Internet of Things (IoT), vehicles and road infrastructure become connected and cooperative, enabling Cooperative Intelligent Transport Systems (C-ITS). C-ITS are transport system of systems that involves many stakeholders from different sectors. While running their own systems and providing services independently, stakeholders cooperate with each other for improving the overall transport performance such as safety, efficiency and sustainability. Massive information on road and traffic is already available and provided through standard services with different protocols. By reusing and composing the available heterogeneous services, novel value-added applications can be developed. This paper introduces a choreography-based service composition platform, i.e. the CHOReVOLUTION Integrated Development and Runtime Environment (IDRE), and it reports on how the IDRE has been successfully exploited to accelerate the reuse-based development of a choreography-based Urban Traffic Coordination (UTC) application. The UTC application takes the shape of eco-driving services that through real-time eco-route evaluation assist the drivers for the most eco-friendly and comfortable driving experience. The eco-driving services are realized through choreography and they are exploited through a mobile app for online navigation. From specification to deployment to execution, the CHOReVOLUTION IDRE has been exploited to support the realization of the UTC application by automatizing the generation of the distributed logic to properly bind, coordinate and adapt the interactions of the involved parties. The benefits brought by CHOReVOLUTION IDRE have been assessed through the evaluation of a set of Key Performance Indicators (KPIs).

A fundamental aspect in performance engineering of wireless networks is optimizing the set of links that can be concurrently activated to meet given signal-to-interference-plus-noise ratio (SINR) thresholds. The solution of this combinatorial problem is the key element in scheduling and cross-layer resource management. In this paper, we assume multiuser decoding (MUD) receivers, which can cancel strongly interfering signals. As a result, in contrast to classical spatial reuse, links being close to each other are more likely to be active concurrently. Our focus is to gauge the gain of successive interference cancelation (SIC) and the simpler, yet instructive, case of parallel interference cancelation (PIC) in the context of optimal link activation (LA). We show that both problems are NP-hard, and we develop compact integer linear programming (ILP) formulations to approach global optimality. We provide an extensive numerical performance evaluation, indicating that, for low to medium SINR thresholds, the improvement is quite substantial, particularly with SIC, whereas for high SINR thresholds, the improvement diminishes, and both schemes perform equally well.

Soft frequency reuse (SFR) has been proposed for enhancing cell-edge performance in OFDMA networks. Previous studies of SFR have used simulations over rather small networks having hexagon-shaped cells. In this paper, we examine the expected performance gain of SFR for networks in realistic radio environments and with irregular cell patterns. We define a performance metric that allows for fast assessment of expected gain of SFR over the service area of large networks. An optimization algorithm is used to tackle the resulting frequency allocation problem. Our approach enables SFR to go beyond the conventional schemes in terms of the number of sub-bands and power setting. We provide a thorough numerical study of SFR in large scale networks and investigate the performance trade-off between cell-edge and cell-center zones to illustrate pros and cons of SFR.