VISIONS Vehicular communication Improvement : solution based on IMS Operational Nodes and Services

Digital services and communications in vehicular scenarios provide the essential assets to improve road transport in several ways like reducing accidents, improving traffic efficiency and optimizing the transport of goods and people. Vehicular communications typically rely on VANET (Vehicular Ad hoc Networks). In these networks vehicles communicate with each other without the need of infrastructure. VANET are mainly oriented to disseminate information to the vehicles in certain geographic area for time critical services like safety warnings but present very challenging requirements that have not been successfully fulfilled nowadays. Some of these challenges are; channel saturation due to simultaneous radio access of many vehicles, routing protocols in topologies that vary rapidly, minimum quality of service assurance and security mechanisms to efficiently detect and neutralize malicious attacks. Vehicular services can be classified in four important groups: Safety, Efficiency, Sustainability and Infotainment. The benefits of these services for the transport sector are clear but many technological and business challenges need to be faced before a real mass market deployment. Service delivery platforms are not prepared for fulfilling the needs of this complex environment with restrictive requirements due to the criticism of some services To overcome this situation, we propose a solution called VISIONS “Vehicular communication Improvement: Solution based on IMS Operational Nodes and Services”. VISIONS leverages on IMS subsystem and NGN enablers, and follows the CALM reference Architecture standardized by ISO. It also avoids the use of Road Side Units (RSUs), reducing complexity and high costs in terms of deployment and maintenance. We demonstrate the benefits in the following areas: 1. VANET networks efficiency. VISIONS provide a mechanism for the vehicles to access valuable information from IMS and its capabilities through a cellular channel. This efficiency improvement will occur in two relevant areas: a. Routing mechanisms. These protocols are responsible of carrying information from a vehicle to another (or a group of vehicles) using multihop mechanisms. We do not propose a new algorithm but the use of VANET topology information provided through our solution to enrich the performance of these protocols. b. Security. Many aspects of security (privacy, key, authentication, access control, revocation mechanisms, etc) are not resolved in vehicular communications. Our solution efficiently disseminates revocation information to neutralize malicious nodes in the VANET. 2. Service delivery platform. It is based on extended enablers, reference architectures, standard protocols and open APIs. By following this approach, we reduce costs and resources for service development, deployment and maintenance. To quantify these benefits in VANET networks, we provide an analytical model of the system and simulate our solution in realistic scenarios. The simulations results demonstrate how VISIONS improves the performance of relevant routing protocols and is more efficient neutralizing security attacks than the widely proposed solutions based on RSUs. Finally, we design an innovative Social Network service based in our platform, explaining how VISIONS facilitate the deployment and usage of complex capabilities. RESUMEN Los servicios digitales y comunicaciones en entornos vehiculares proporcionan herramientas esenciales para mejorar el transporte por carretera; reduciendo el número de accidentes, mejorando la eficiencia del tráfico y optimizando el transporte de mercancías y personas. Las comunicaciones vehiculares generalmente están basadas en redes VANET (Vehicular Ad hoc Networks). En dichas redes, los vehículos se comunican entre sí sin necesidad de infraestructura. Las redes VANET están principalmente orientadas a difundir información (por ejemplo advertencias de seguridad) a los vehículos en determinadas zonas geográficas, pero presentan unos requisitos muy exigentes que no se han resuelto con éxito hasta la fecha. Algunos de estos retos son; saturación del canal de acceso de radio debido al acceso simultáneo de múltiples vehículos, la eficiencia de protocolos de encaminamiento en topologías que varían rápidamente, la calidad de servicio (QoS) y los mecanismos de seguridad para detectar y neutralizar los ataques maliciosos de manera eficiente. Los servicios vehiculares pueden clasificarse en cuatro grupos: Seguridad, Eficiencia del tráfico, Sostenibilidad, e Infotainment (información y entretenimiento). Los beneficios de estos servicios para el sector son claros, pero es necesario resolver muchos desafíos tecnológicos y de negocio antes de una implementación real. Las actuales plataformas de despliegue de servicios no están preparadas para satisfacer las necesidades de este complejo entorno con requisitos muy restrictivos debido a la criticidad de algunas aplicaciones. Con el objetivo de mejorar esta situación, proponemos una solución llamada VISIONS “Vehicular communication Improvement: Solution based on IMS Operational Nodes and Services”. VISIONS se basa en el subsistema IMS, las capacidades NGN y es compatible con la arquitectura de referencia CALM estandarizado por ISO para sistemas de transporte. También evita el uso de elementos en las carreteras, conocidos como Road Side Units (RSU), reduciendo la complejidad y los altos costes de despliegue y mantenimiento. A lo largo de la tesis, demostramos los beneficios en las siguientes áreas: 1. Eficiencia en redes VANET. VISIONS proporciona un mecanismo para que los vehículos accedan a información valiosa proporcionada por IMS y sus capacidades a través de un canal de celular. Dicho mecanismo contribuye a la mejora de dos áreas importantes: a. Mecanismos de encaminamiento. Estos protocolos son responsables de llevar información de un vehículo a otro (o a un grupo de vehículos) utilizando múltiples saltos. No proponemos un nuevo algoritmo de encaminamiento, sino el uso de información topológica de la red VANET a través de nuestra solución para enriquecer el funcionamiento de los protocolos más relevantes. b. Seguridad. Muchos aspectos de la seguridad (privacidad, gestión de claves, autenticación, control de acceso, mecanismos de revocación, etc) no están resueltos en las comunicaciones vehiculares. Nuestra solución difunde de manera eficiente la información de revocación para neutralizar los nodos maliciosos en la red. 2. Plataforma de despliegue de servicios. Está basada en capacidades NGN, arquitecturas de referencia, protocolos estándar y APIs abiertos. Siguiendo este enfoque, reducimos costes y optimizamos procesos para el desarrollo, despliegue y mantenimiento de servicios vehiculares. Para cuantificar estos beneficios en las redes VANET, ofrecemos un modelo de analítico del sistema y simulamos nuestra solución en escenarios realistas. Los resultados de las simulaciones muestran cómo VISIONS mejora el rendimiento de los protocolos de encaminamiento relevantes y neutraliza los ataques a la seguridad de forma más eficientes que las soluciones basadas en RSU. Por último, diseñamos un innovador servicio de red social basado en nuestra plataforma, explicando cómo VISIONS facilita el despliegue y el uso de las capacidades NGN.

Adaptive rate control of dedicated short range communications based vehicle networks for road safety applications

Dedicated Short Range Communication (DSRC) is a promising technique for vehicle ad-hoc network (VANET) and collaborative road safety applications. As road safety applications require strict quality of services (QoS) from the VANET, it is crucial for DSRC to provide timely and reliable communications to make safety applications successful. In this paper we propose two adaptive message rate control algorithms for low priority safety messages, in order to provide highly available channel for high priority emergency messages while improve channel utilization. In the algorithms each vehicle monitors channel loads and independently controls message rate by a modified additive increase and multiplicative decrease (AIMD) method. Simulation results demonstrated the effectiveness of the proposed rate control algorithms in adapting to dynamic traffic load.

Effect of the base station antenna beam tilting on energy consumption in cellular networks

The objective of this paper is to combine the antenna downtilt selection with the cell size selection in order to reduce the overall radio frequency (RF) transmission power in the homogeneous High-Speed Packet Downlink (HSDPA) cellular radio access network (RAN). The analysis is based on the concept of small cells deployment. The energy consumption ratio (ECR) and the energy reduction gain (ERG) of the cellular RAN are calculated for different antenna tilts when the cell size is being reduced for a given user density and service area. The results have shown that a suitable antenna tilt and the RF power setting can achieve an overall energy reduction of up to 82.56%. Equally, our results demonstrate that a small cell deployment can considerably reduce the overall energy consumption of a cellular network.

Practical network coding for two way relay channels in LTE networks

In this paper, the implementation aspects and constraints of the simplest network coding (NC) schemes for a two-way relay channel (TWRC) composed of a user equipment (mobile terminal), an LTE relay station (RS) and an LTE base station (eNB) are considered in order to assess the usefulness of the NC in more realistic scenarios. The information exchange rate gain (IERG), the energy reduction gain (ERG) and the resource utilization gain (RUG) of the NC schemes with and without subcarrier division duplexing (SDD) are obtained by computer simulations. The usefulness of the NC schemes are evaluated for varying traffic load levels, the geographical distances between the nodes, the RS transmit powers, and the maximum numbers of retransmissions. Simulation results show that the NC schemes with and without SDD, have the throughput gains 0.5% and 25%, the ERGs 7 - 12% and 16 - 25%, and the RUGs 0.5 - 3.2%, respectively. It is found that the NC can provide performance gains also for the users at the cell edge. Furthermore, the ERGs of the NC increase with the transmit power of the relay while the ERGs of the NC remain the same even when the maximum number of retransmissions is reduced.

Enhanced slotted aloha protocols for underwater sensor networks with large propagation delay

Recently underwater sensor networks (UWSN) attracted large research interests. Medium access control (MAC) is one of the major challenges faced by UWSN due to the large propagation delay and narrow channel bandwidth of acoustic communications used for UWSN. Widely used slotted aloha (S-Aloha) protocol suffers large performance loss in UWSNs, which can only achieve performance close to pure aloha (P-Aloha). In this paper we theoretically model the performances of S-Aloha and P-Aloha protocols and analyze the adverse impact of propagation delay. According to the observation on the performances of S-Aloha protocol we propose two enhanced S-Aloha protocols in order to minimize the adverse impact of propagation delay on S-Aloha protocol. The first enhancement is a synchronized arrival S-Aloha (SA-Aloha) protocol, in which frames are transmitted at carefully calculated time to align the frame arrival time with the start of time slots. Propagation delay is taken into consideration in the calculation of transmit time. As estimation error on propagation delay may exist and can affect network performance, an improved SA-Aloha (denoted by ISA-Aloha) is proposed, which adjusts the slot size according to the range of delay estimation errors. Simulation results show that both SA-Aloha and ISA-Aloha perform remarkably better than S-Aloha and P-Aloha for UWSN, and ISA-Aloha is more robust even when the propagation delay estimation error is large. © 2011 IEEE.

Energy aware data gathering based on adaptive modulation scaling in wireless sensor networks

Energy consumption has been a key concern of data gathering in wireless sensor networks. Previous research works show that modulation scaling is an efficient technique to reduce energy consumption. However, such technique will also impact on both packet delivery latency and packet loss, therefore, may result in adverse effects on the qualities of applications. In this paper, we study the problem of modulation scaling and energy-optimization. A mathematical model is proposed to analyze the impact of modulation scaling on the overall energy consumption, end-to-end mean delivery latency and mean packet loss rate. A centralized optimal management mechanism is developed based on the model, which adaptively adjusts the modulation levels to minimize energy consumption while ensuring the QoS for data gathering. Experimental results show that the management mechanism saves significant energy in all the investigated scenarios. Some valuable results are also observed in the experiments. © 2004 IEEE.

Performance evaluation of adaptive context aware rate selection algorithm (ACARS) for road safety applications in vehicular network

One of the major drawbacks for mobile nodes in wireless networks is power management. Our goal is to evaluate the performance power control scheme to be used to reduce network congestion, improve quality of service and collision avoidance in vehicular network and road safety application. Some of the importance of power control (PC) are improving spatial reuse, and increasing network capacity in mobile wireless communications. In this simulation we have evaluated the performance of existing rate algorithms compared with context Aware Rate selection algorithm (ACARS) and also seen the performance of ACARS and how it can be applied to road safety, improve network control and power management. Result shows that ACARS is able to minimize the total transmit power in the presence of propagation processes and mobility of vehicles, by adapting to the fast varying channels conditions with the Path loss exponent values that was used for that environment which is shown in the network simulation parameter. Our results have shown that ACARS is a very robust algorithm which performs very well with the effect of propagation processes that is prone to every transmitted signal in mobile networks. © 2013 IEEE.

Outage performance of cognitive cooperative networks with relay selection over double-Rayleigh fading channels

This study considers a dual-hop cognitive inter-vehicular relay-assisted communication system where all
communication links are non-line of sight ones and their fading is modelled by the double Rayleigh fading distribution.
Road-side relays (or access points) implementing the decode-and-forward relaying protocol are employed and one of
them is selected according to a predetermined policy to enable communication between vehicles. The performance of
the considered cognitive cooperative system is investigated for Kth best partial and full relay selection (RS) as well as
for two distinct fading scenarios. In the first scenario, all channels are double Rayleigh distributed. In the second
scenario, only the secondary source to relay and relay to destination channels are considered to be subject to double
Rayleigh fading whereas, channels between the secondary transmitters and the primary user are modelled by the
Rayleigh distribution. Exact and approximate expressions for the outage probability performance for all considered RS
policies and fading scenarios are presented. In addition to the analytical results, complementary computer simulated
performance evaluation results have been obtained by means of Monte Carlo simulations. The perfect match between
these two sets of results has verified the accuracy of the proposed mathematical analysis.

An Efficient Precoder Design for Multiuser MIMO Cognitive Radio Networks with Interference Constraints

We consider a linear precoder design for an underlay cognitive radio multiple-input multiple-output broadcast channel, where the secondary system consisting of a secondary base-station (BS) and a group of secondary users (SUs) is allowed to share the same spectrum with the primary system. All the transceivers are equipped with multiple antennas, each of which has its own maximum power constraint. Assuming zero-forcing method to eliminate the multiuser interference, we study the sum rate maximization problem for the secondary system subject to both per-antenna power constraints at the secondary BS and the interference power constraints at the primary users. The problem of interest differs from the ones studied previously that often assumed a sum power constraint and/or single antenna employed at either both the primary and secondary receivers or the primary receivers. To develop an efficient numerical algorithm, we first invoke the rank relaxation method to transform the considered problem into a convex-concave problem based on a downlink-uplink result. We then propose a barrier interior-point method to solve the resulting saddle point problem. In particular, in each iteration of the proposed method we find the Newton step by solving a system of discrete-time Sylvester equations, which help reduce the complexity significantly, compared to the conventional method. Simulation results are provided to demonstrate fast convergence and effectiveness of the proposed algorithm. 

The Role of B5G UAV-Aided Mobile Networks

With the advent of 5G, several novel network paradigms and technologies have been proposed to fulfil the key requirements imposed. Flexibility, efficiency and scalability, along with sustainability and convenience for expenditure have to be addressed in targeting these brand new needs. Among novel paradigms introduced in the scientific literature in recent years, a constant and increasing interest lies in the use of unmanned aerial vehicles (UAVs) as network nodes supporting the legacy terrestrial network for service provision. Their inherent features of moving nodes make them able to be deployed on-demand in real-time. Which, in practical terms, means having them acting as a base station (BS) when and where there is the highest need. This thesis investigates then the potential role of UAV-aided mobile radio networks, in order to validate the concept of adding an aerial network component and assess the system performance, from early to later stages of its deployment. This study is intended for 5G and beyond systems, to allow time for the technology to mature. Since advantages can be manyfold, the aerial network component is considered at the network layer under several aspects, from connectivity to radio resource management. A particular emphasis is given to trajectory design, because of the efficiency and flexibility it potentially adds to the infrastructure. Two different frameworks have been proposed, to take into account both a re-adaptable heuristic and an optimal solution. Moreover, diverse use cases are taken under analysis, from mobile broadband to machine and vehicular communications. The thesis aim is thus to discuss the potential and advantages of UAV-aided systems from a broad perspective. Results demonstrate that the technology has good prospects for diverse scenarios with a few arrangements.

Trajectory Planning in UAV-Aided Wireless Networks Via Reinforcement Learning

This thesis is focused on the design of a flexible, dynamic and innovative telecommunication's system for future 6G applications on vehicular communications. The system is based on the development of drones acting as mobile base stations in an urban scenario to cope with the increasing traffic demand and avoid network's congestion conditions. In particular, the exploitation of Reinforcement Learning algorithms is used to let the drone learn autonomously how to behave in a scenario full of obstacles with the goal of tracking and serve the maximum number of moving vehicles, by at the same time, minimizing the energy consumed to perform its tasks. This project is an extraordinary opportunity to open the doors to a new way of applying and develop telecommunications in an urban scenario by mixing it to the rising world of the Artificial Intelligence.

Contrasting Effects Of Land Use Intensity And Exotic Host Plants On The Specialization Of Interactions In Plant-herbivore Networks.

Human land use tends to decrease the diversity of native plant species and facilitate the invasion and establishment of exotic ones. Such changes in land use and plant community composition usually have negative impacts on the assemblages of native herbivorous insects. Highly specialized herbivores are expected to be especially sensitive to land use intensification and the presence of exotic plant species because they are neither capable of consuming alternative plant species of the native flora nor exotic plant species. Therefore, higher levels of land use intensity might reduce the proportion of highly specialized herbivores, which ultimately would lead to changes in the specialization of interactions in plant-herbivore networks. This study investigates the community-wide effects of land use intensity on the degree of specialization of 72 plant-herbivore networks, including effects mediated by the increase in the proportion of exotic plant species. Contrary to our expectation, the net effect of land use intensity on network specialization was positive. However, this positive effect of land use intensity was partially canceled by an opposite effect of the proportion of exotic plant species on network specialization. When we analyzed networks composed exclusively of endophagous herbivores separately from those composed exclusively of exophagous herbivores, we found that only endophages showed a consistent change in network specialization at higher land use levels. Altogether, these results indicate that land use intensity is an important ecological driver of network specialization, by way of reducing the local host range of herbivore guilds with highly specialized feeding habits. However, because the effect of land use intensity is offset by an opposite effect owing to the proportion of exotic host species, the net effect of land use in a given herbivore assemblage will likely depend on the extent of the replacement of native host species with exotic ones.

Complex networks: the key to systems biology

Though introduced recently, complex networks research has grown steadily because of its potential to represent, characterize and model a wide range of intricate natural systems and phenomena. Because of the intrinsic complexity and systemic organization of life, complex networks provide a specially promising framework for systems biology investigation. The current article is an up-to-date review of the major developments related to the application of complex networks in biology, with special attention focused on the more recent literature. The main concepts and models of complex networks are presented and illustrated in an accessible fashion. Three main types of networks are covered: transcriptional regulatory networks, protein-protein interaction networks and metabolic networks. The key role of complex networks for systems biology is extensively illustrated by several of the papers reviewed.

Neural networks and statistical analysis for classification of corneal videokeratography maps based on Zernike coefficients: a quantitative comparison

PURPOSE: The main goal of this study was to develop and compare two different techniques for classification of specific types of corneal shapes when Zernike coefficients are used as inputs. A feed-forward artificial Neural Network (NN) and discriminant analysis (DA) techniques were used. METHODS: The inputs both for the NN and DA were the first 15 standard Zernike coefficients for 80 previously classified corneal elevation data files from an Eyesys System 2000 Videokeratograph (VK), installed at the Departamento de Oftalmologia of the Escola Paulista de Medicina, São Paulo. The NN had 5 output neurons which were associated with 5 typical corneal shapes: keratoconus, with-the-rule astigmatism, against-the-rule astigmatism, "regular" or "normal" shape and post-PRK. RESULTS: The NN and DA responses were statistically analyzed in terms of precision ([true positive+true negative]/total number of cases). Mean overall results for all cases for the NN and DA techniques were, respectively, 94% and 84.8%. CONCLUSION: Although we used a relatively small database, results obtained in the present study indicate that Zernike polynomials as descriptors of corneal shape may be a reliable parameter as input data for diagnostic automation of VK maps, using either NN or DA.

Evaluation of follicular lymphoid depletion in the Bursa of Fabricius: an alternative methodology using digital image analysis and artificial neural networks

Fifty Bursa of Fabricius (BF) were examined by conventional optical microscopy and digital images were acquired and processed using Matlab® 6.5 software. The Artificial Neuronal Network (ANN) was generated using Neuroshell® Classifier software and the optical and digital data were compared. The ANN was able to make a comparable classification of digital and optical scores. The use of ANN was able to classify correctly the majority of the follicles, reaching sensibility and specificity of 89% and 96%, respectively. When the follicles were scored and grouped in a binary fashion the sensibility increased to 90% and obtained the maximum value for the specificity of 92%. These results demonstrate that the use of digital image analysis and ANN is a useful tool for the pathological classification of the BF lymphoid depletion. In addition it provides objective results that allow measuring the dimension of the error in the diagnosis and classification therefore making comparison between databases feasible.