On the performance of social-based and location-aware forwarding strategies in urban vehicular networks

High vehicular mobility in urban scenarios originates inter-vehicles communication discontinuities, a highly important factor when designing a forwarding strategy for vehicular networks. Store, carry and forward mechanisms enable the usage of vehicular networks in a large set of applications, such as sensor data collection in IoT, contributing to smart city platforms. This work evaluates the performance of several location-based and social-aware forwarding schemes through emulations and in a real scenario. Gateway Location Awareness (GLA), a location-aware ranking classification, makes use of velocity, heading angle and distance to the gateway, to select the vehicles with higher chance to deliver the information in a shorter period of time, thus differentiating nodes through their movement patterns. Aging Social-Aware Ranking (ASAR) exploits the social behavior of each vehicle, where nodes are ranked based on a historical contact table, differentiating vehicles with a high number of contacts from those who barely contact with other vehicles. To merge both location and social aforementioned algorithms, a HYBRID approach emerges, thus generating a more intelligent mechanism. For each strategy, we evaluate the influence of several parameters in the network performance, as well as we comparatively evaluate the strategies in different scenarios. Experiment results, obtained both in emulated (with real traces of both mobility and vehicular connectivity from a real city-scale urban vehicular network) and real scenarios, show the performance of GLA, ASAR and HYBRID schemes, and their results are compared to lower- and upper-bounds. The obtained results show that these strategies are a good tradeoff to maximize data delivery ratio and minimize network overhead, while making use of mobile networks as a smart city network infrastructure.publishe

From MANET to people-centric networking: Milestones and open research challenges

In this paper, we discuss the state of the art of (mobile) multi-hop ad hoc networking with the aim to present the current status of the research activities and identify the consolidated research areas, with limited research opportunities, and the hot and emerging research areas for which further research is required. We start by briefly discussing the MANET paradigm, and why the research on MANET protocols is now a cold research topic. Then we analyze the active research areas. Specifically, after discussing the wireless-network technologies, we analyze four successful ad hoc networking paradigms, mesh networks, opportunistic networks, vehicular networks, and sensor networks that emerged from the MANET world. We also present an emerging research direction in the multi-hop ad hoc networking field: people centric networking, triggered by the increasing penetration of the smartphones in everyday life, which is generating a people-centric revolution in computing and communications

Adaptive Network Densification with Small Cell Mobile Base Stations Carried by Vehicles

1noL'abstract è presente nell'allegato / the abstract is in the attachmentopen676. INGEGNERIA ELETTRICAnopartially_openembargoed_20211014Mohammadnia, Foroog

Vehicle classification in intelligent transport systems: an overview, methods and software perspective

Vehicle Classification (VC) is a key element of Intelligent Transportation Systems (ITS). Diverse ranges of ITS applications like security systems, surveillance frameworks, fleet monitoring, traffic safety, and automated parking are using VC. Basically, in the current VC methods, vehicles are classified locally as a vehicle passes through a monitoring area, by fixed sensors or using a compound method. This paper presents a pervasive study on the state of the art of VC methods. We introduce a detailed VC taxonomy and explore the different kinds of traffic information that can be extracted via each method. Subsequently, traditional and cutting edge VC systems are investigated from different aspects. Specifically, strengths and shortcomings of the existing VC methods are discussed and real-time alternatives like Vehicular Ad-hoc Networks (VANETs) are investigated to convey physical as well as kinematic characteristics of the vehicles. Finally, we review a broad range of soft computing solutions involved in VC in the context of machine learning, neural networks, miscellaneous features, models and other methods

VANET-enabled eco-friendly road characteristics-aware routing for vehicular traffic

There is growing awareness of the dangers of climate change caused by greenhouse gases. In the coming decades this could result in numerous disasters such as heat-waves, flooding and crop failures. A major contributor to the total amount of greenhouse gas emissions is the transport sector, particularly private vehicles. Traffic congestion involving private vehicles also causes a lot of wasted time and stress to commuters. At the same time new wireless technologies such as Vehicular Ad-Hoc Networks (VANETs) are being developed which could allow vehicles to communicate with each other. These could enable a number of innovative schemes to reduce traffic congestion and greenhouse gas emissions. 1) EcoTrec is a VANET-based system which allows vehicles to exchange messages regarding traffic congestion and road conditions, such as roughness and gradient. Each vehicle uses the messages it has received to build a model of nearby roads and the traffic on them. The EcoTrec Algorithm then recommends the most fuel efficient route for the vehicles to follow. 2) Time-Ants is a swarm based algorithm that considers not only the amount of cars in the spatial domain but also the amoumt in the time domain. This allows the system to build a model of the traffic congestion throughout the day. As traffic patterns are broadly similar for weekdays this gives us a good idea of what traffic will be like allowing us to route the vehicles more efficiently using the Time-Ants Algorithm. 3) Electric Vehicle enhanced Dedicated Bus Lanes (E-DBL) proposes allowing electric vehicles onto the bus lanes. Such an approach could allow a reduction in traffic congestion on the regular lanes without greatly impeding the buses. It would also encourage uptake of electric vehicles. 4) A comprehensive survey of issues associated with communication centred traffic management systems was carried out

Prediction-based techniques for the optimization of mobile networks

Mención Internacional en el título de doctorMobile cellular networks are complex system whose behavior is characterized by the superposition of several random phenomena, most of which, related to human activities, such as mobility, communications and network usage. However, when observed in their totality, the many individual components merge into more deterministic patterns and trends start to be identifiable and predictable. In this thesis we analyze a recent branch of network optimization that is commonly referred to as anticipatory networking and that entails the combination of prediction solutions and network optimization schemes. The main intuition behind anticipatory networking is that knowing in advance what is going on in the network can help understanding potentially severe problems and mitigate their impact by applying solution when they are still in their initial states. Conversely, network forecast might also indicate a future improvement in the overall network condition (i.e. load reduction or better signal quality reported from users). In such a case, resources can be assigned more sparingly requiring users to rely on buffered information while waiting for the better condition when it will be more convenient to grant more resources. In the beginning of this thesis we will survey the current anticipatory networking panorama and the many prediction and optimization solutions proposed so far. In the main body of the work, we will propose our novel solutions to the problem, the tools and methodologies we designed to evaluate them and to perform a real world evaluation of our schemes. By the end of this work it will be clear that not only is anticipatory networking a very promising theoretical framework, but also that it is feasible and it can deliver substantial benefit to current and next generation mobile networks. In fact, with both our theoretical and practical results we show evidences that more than one third of the resources can be saved and even larger gain can be achieved for data rate enhancements.Programa Oficial de Doctorado en Ingeniería TelemáticaPresidente: Albert Banchs Roca.- Presidente: Pablo Serrano Yañez-Mingot.- Secretario: Jorge Ortín Gracia.- Vocal: Guevara Noubi