Computational Intelligence Inspired Data Delivery for Vehicle-to-Roadside Communications

We propose a vehicle-to-roadside communication protocol based on distributed clustering where a coalitional game approach is used to stimulate the vehicles to join a cluster, and a fuzzy logic algorithm is employed to generate stable clusters by considering multiple metrics of vehicle velocity, moving pattern, and signal qualities between vehicles. A reinforcement learning algorithm with game theory based reward allocation is employed to guide each vehicle to select the route that can maximize the whole network performance. The protocol is integrated with a multi-hop data delivery virtualization scheme that works on the top of the transport layer and provides high performance for multi-hop end-to-end data transmissions. We conduct realistic computer simulations to show the performance advantage of the protocol over other approaches

Recent Developments on Mobile Ad-Hoc Networks and Vehicular Ad-Hoc Networks

This book presents collective works published in the recent Special Issue (SI) entitled "Recent Developments on Mobile Ad-Hoc Networks and Vehicular Ad-Hoc Networks”. These works expose the readership to the latest solutions and techniques for MANETs and VANETs. They cover interesting topics such as power-aware optimization solutions for MANETs, data dissemination in VANETs, adaptive multi-hop broadcast schemes for VANETs, multi-metric routing protocols for VANETs, and incentive mechanisms to encourage the distribution of information in VANETs. The book demonstrates pioneering work in these fields, investigates novel solutions and methods, and discusses future trends in these field

Mobile Ad Hoc Networks

Guiding readers through the basics of these rapidly emerging networks to more advanced concepts and future expectations, Mobile Ad hoc Networks: Current Status and Future Trends identifies and examines the most pressing research issues in Mobile Ad hoc Networks (MANETs). Containing the contributions of leading researchers, industry professionals, and academics, this forward-looking reference provides an authoritative perspective of the state of the art in MANETs. The book includes surveys of recent publications that investigate key areas of interest such as limited resources and the mobility of mobile nodes. It considers routing, multicast, energy, security, channel assignment, and ensuring quality of service. Also suitable as a text for graduate students, the book is organized into three sections: Fundamentals of MANET Modeling and Simulation—Describes how MANETs operate and perform through simulations and models Communication Protocols of MANETs—Presents cutting-edge research on key issues, including MAC layer issues and routing in high mobility Future Networks Inspired By MANETs—Tackles open research issues and emerging trends Illustrating the role MANETs are likely to play in future networks, this book supplies the foundation and insight you will need to make your own contributions to the field. It includes coverage of routing protocols, modeling and simulations tools, intelligent optimization techniques to multicriteria routing, security issues in FHAMIPv6, connecting moving smart objects to the Internet, underwater sensor networks, wireless mesh network architecture and protocols, adaptive routing provision using Bayesian inference, and adaptive flow control in transport layer using genetic algorithms

Mobile Ad Hoc Networks

Guiding readers through the basics of these rapidly emerging networks to more advanced concepts and future expectations, Mobile Ad hoc Networks: Current Status and Future Trends identifies and examines the most pressing research issues in Mobile Ad hoc Networks (MANETs). Containing the contributions of leading researchers, industry professionals, and academics, this forward-looking reference provides an authoritative perspective of the state of the art in MANETs. The book includes surveys of recent publications that investigate key areas of interest such as limited resources and the mobility of mobile nodes. It considers routing, multicast, energy, security, channel assignment, and ensuring quality of service. Also suitable as a text for graduate students, the book is organized into three sections: Fundamentals of MANET Modeling and Simulation—Describes how MANETs operate and perform through simulations and models Communication Protocols of MANETs—Presents cutting-edge research on key issues, including MAC layer issues and routing in high mobility Future Networks Inspired By MANETs—Tackles open research issues and emerging trends Illustrating the role MANETs are likely to play in future networks, this book supplies the foundation and insight you will need to make your own contributions to the field. It includes coverage of routing protocols, modeling and simulations tools, intelligent optimization techniques to multicriteria routing, security issues in FHAMIPv6, connecting moving smart objects to the Internet, underwater sensor networks, wireless mesh network architecture and protocols, adaptive routing provision using Bayesian inference, and adaptive flow control in transport layer using genetic algorithms

Modeling and Analysis of Location Service Management in Vehicular Ad Hoc Networks

Recent technological advances in wireless communication and the pervasiveness of various wireless communication devices have offered novel and promising solutions to enable vehicles to communicate with each other, establishing a decentralized communication system. An emerging solution in this area is the Vehicular Ad Hoc Networks (VANETs), in which vehicles cooperate in receiving and delivering messages to each other. VANETs can provide a viable alternative in situations where existing infrastructure communication systems become overloaded, fail (due for instance to natural disaster), or inconvenient to use. Nevertheless, the success of VANETs revolves around a number of key elements, an important one of which is the way messages are routed between sources and destinations. Without an effective message routing strategy VANETs' success will continue to be limited. In order for messages to be routed to a destination effectively, the location of the destination must be determined. Since vehicles move in relatively fast and in a random manner, determining the location (hence the optimal message routing path) of (to) the destination vehicle constitutes a major challenge. Recent approaches for tackling this challenge have resulted in a number of Location Service Management Protocols. Though these protocols have demonstrated good potential, they still suffer from a number of impediments, including, signaling volume (particularly in large scale VANETs), inability to deal with network voids and inability to leverage locality for communication between the network nodes. In this thesis, a Region-based Location Service Management Protocol (RLSMP) is proposed. The protocol is a self-organizing framework that uses message aggregation and geographical clustering to minimize the volume of signalling overhead. To the best of my knowledge, RLSMP is the first protocol that uses message aggregation in both updating and querying, and as such it promises scalability, locality awareness, and fault tolerance. Location service management further addresses the issue of routing location updating and querying messages. Updating and querying messages should be exchanged between the network nodes and the location servers with minimum delay. This necessity introduces a persuasive need to support Quality of Service (QoS) routing in VANETs. To mitigate the QoS routing challenge in VANETs, the thesis proposes an Adaptive Message Routing (AMR) protocol that utilizes the network's local topology information in order to find the route with minimum end-to-end delay, while maintaining the required thresholds for connectivity probability and hop count. The QoS routing problem is formulated as a constrained optimization problem for which a genetic algorithm is proposed. The thesis presents experiments to validate the proposed protocol and test its performance under various network conditions

Suporte a gerenciamento do trânsito baseado em computação na névoa para os sistemas de transporte inteligentes

Orientadores: Leandro Aparecido Villas, Daniel Ludovico GuidoniTese (doutorado) ¿ Universidade Estadual de Campinas, Instituto de ComputaçãoResumo: O trânsito nos grandes centros urbanos contribui com problemas que vão desde diminuição da qualidade de vida e segurança da população até o aumento de custos financeiros às pessoas, cidades e empresas. Um dos motivos para um maior tráfego de veículos é o vertiginoso crescimento populacional dos centros urbanos. Além disso, o fluxo de veículos é prejudicado por situações adversas recorrentes nas vias, como o aumento súbito do tráfego durante os horários de pico, gargalos nas infraestruturas de transporte, e acidentes de trânsito. Com o avanço das tecnologias de comunicação, processamento e sensoriamento, os Sistemas de Transporte Inteligentes (ITS) surgem como uma alternativa para mitigar esses problemas. A interoperabilidade dos ITS com novas tecnologias tais como as redes veiculares (VANETs) e computação em névoa, os tornam mais promissores e eficazes. As VANETs preveem que veículos possuam poder computacional e capacidade de comunicação sem fio com outros veículos e com as infraestruturas fixa de comunicação, assim, uma nova gama de serviços de segurança e entretenimento aos motoristas e passageiros podem ser desenvolvidas. Entretanto, estes tipos de serviços, em especial o de gerenciamento de trânsito, demandam uma análise contínua das condições de fluxo de veículos nas vias e um vasto recurso de rede e processamento, tornando o desenvolvimento de soluções para ITS mais complexo e de difícil escalabilidade. A computação em névoa é uma infraestrutura de computação descentralizada na qual dados, processamento, armazenamento e aplicações são distribuídos na borda da rede, assim, aumentando a escalabilidade do sistema. Na literatura, os sistemas de gerenciamento de tráfego não tratam de maneira adequada o problema de escalabilidade, implicando em problemas relacionados ao balanceamento de carga e tempo de resposta. Esta tese de doutorado propõe um sistema de gerenciamento de tráfego baseado no paradigma de computação em névoa, para detectar, classificar e controlar o congestionamento de tráfego. O sistema proposto apresenta um framework distribuído e escalável que reduz os problemas supracitados em relação ao estado da arte. Para tanto, utilizando da natureza distribuída da computação em névoa, a solução implementa um algoritmo de roteamento probabilístico que faz o balanceamento do tráfego e evita o problema de deslocamento de congestionamentos para outras regiões. Utilizando às características da computação em névoa, foi desenvolvida uma metodologia distribuída baseada em regiões que faz a coleta de dados e classificação das vias em relação às condições do trânsito compartilhadas pelos veículos. Finalmente, foi desenvolvido um conjunto de algoritmos/protocolos de comunicação que comparado com outras soluções da literatura, reduz a perda de pacotes e o número de mensagens transmitidas. O serviço proposto foi comparado extensivamente com outras soluções da literatura em relação às métricas de trânsito, onde o sistema proposto foi capaz de reduzir em até 70% o tempo parado e em até 49% o planning time index. Considerando as métricas de comunicação, o serviço proposto é capaz de reduzir em até 12% a colisão de pacotes alcançando uma cobertura de 98% do cenário. Os resultados mostram que o framework baseado em computação em névoa desenvolvido, melhora o fluxo de veículos de forma eficiente e escalávelAbstract: Traffic in large urban centers contributes to problems that range from decreasing the population¿s quality of life and security to increasing financial costs for people, cities, and companies. One of the reasons for increased vehicle traffic is the population growth in urban centers. Moreover, vehicle flow is hampered by recurring adverse situations on roads, such as the sudden increase in vehicle traffic during peak hours, bottlenecks in transportation infrastructure, and traffic accidents. Considering the advance of communication, processing, and sensing technologies, Intelligent Transport Systems (ITS) have emerged as an alternative to mitigate these problems. The interoperability of ITS with new technologies, such as vehicular networks (VANETs) and Fog computing, make them more promising and effective. VANETs ensure that vehicles have the computing power and wireless communication capabilities with other vehicles and with fixed communication infrastructures; therefore, a new range of security and entertainment services for drivers and passengers can be developed. However, these types of services, especially traffic management, demand a continuous analysis of vehicle flow conditions on roads and a huge network and processing resource, making the development of ITS solutions more complex and difficult to scale. Fog computing is a decentralized computing infrastructure in which data, processing, storage, and applications are distributed at the network edge, thereby increasing the system¿s scalability. In the literature, traffic management systems do not adequately address the scalability problem, resulting in load balancing and response time problems. This doctoral thesis proposes a traffic management system based on the Fog computing paradigm to detect, classify, and control traffic congestion. The proposed system presents a distributed and scalable framework that reduces the aforementioned problems in relation to state of the art. Therefore, using Fog computing¿s distributed nature, the solution implements a probabilistic routing algorithm that balances traffic and avoids the problem of congestion displacement to other regions. Using the characteristics of Fog computing, a distributed methodology was developed based on regions that collect data and classify the roads concerning the traffic conditions shared by the vehicles. Finally, a set of communication algorithms/protocols was developed which, compared with other literature solutions, reduces packet loss and the number of messages transmitted. The proposed service was compared extensively with other solutions in the literature regarding traffic metrics, where the proposed system was able to reduce downtime by up to 70% and up to 49% of the planning time index. Considering communication metrics, the proposed service can reduce packet collision by up to 12% reaching 98% coverage of the scenario. The results show that the framework based on Fog computing developed improves the vehicles¿ flow efficiently and in a scalable wayDoutoradoCiência da ComputaçãoDoutor em Ciência da Computaçã

Secure Authentication and Privacy-Preserving Techniques in Vehicular Ad-hoc NETworks (VANETs)

In the last decade, there has been growing interest in Vehicular Ad Hoc NETworks (VANETs). Today car manufacturers have already started to equip vehicles with sophisticated sensors that can provide many assistive features such as front collision avoidance, automatic lane tracking, partial autonomous driving, suggestive lane changing, and so on. Such technological advancements are enabling the adoption of VANETs not only to provide safer and more comfortable driving experience but also provide many other useful services to the driver as well as passengers of a vehicle. However, privacy, authentication and secure message dissemination are some of the main issues that need to be thoroughly addressed and solved for the widespread adoption/deployment of VANETs. Given the importance of these issues, researchers have spent a lot of effort in these areas over the last decade. We present an overview of the following issues that arise in VANETs: privacy, authentication, and secure message dissemination. Then we present a comprehensive review of various solutions proposed in the last 10 years which address these issues. Our survey sheds light on some open issues that need to be addressed in the future