Ant-inspired Interaction Networks For Decentralized Vehicular Traffic Congestion Control

Mimicking the autonomous behaviors of animals and their adaptability to changing or foreign environments lead to the development of swarm intelligence techniques such as ant colony optimization (ACO) and particle swarm optimization (PSO) now widely used to tackle a variety of optimization problems. The aim of this dissertation is to develop an alternative swarm intelligence model geared toward decentralized congestion avoidance and to determine qualities of the model suitable for use in a transportation network. A microscopic multi-agent interaction network inspired by insect foraging behaviors, especially ants, was developed and consequently adapted to prioritize the avoidance of congestion, evaluated as perceived density of other agents in the immediate environment extrapolated from the occurrence of direct interactions between agents, while foraging for food outside the base/nest. The agents eschew pheromone trails or other forms of stigmergic communication in favor of these direct interactions whose rate is the primary motivator for the agents\u27 decision making process. The decision making process at the core of the multi-agent interaction network is consequently transferred to transportation networks utilizing vehicular ad-hoc networks (VANETs) for communication between vehicles. Direct interactions are replaced by dedicated short range communications for wireless access in vehicular environments (DSRC/WAVE) messages used for a variety of applications like left turn assist, intersection collision avoidance, or cooperative adaptive cruise control. Each vehicle correlates the traffic on the wireless network with congestion in the transportation network and consequently decides whether to reroute and, if so, what alternate route to take in a decentralized, non-deterministic manner. The algorithm has been shown to increase throughput and decrease mean travel times significantly while not requiring access to centralized infrastructure or up-to-date traffic information

Exploiting vehicular social networks and dynamic clustering to enhance urban mobility management

Transport authorities are employing advanced traffic management system (ATMS) to improve vehicular traffic management efficiency. ATMS currently uses intelligent traffic lights and sensors distributed along the roads to achieve its goals. Furthermore, there are other promising technologies that can be applied more efficiently in place of the abovementioned ones, such as vehicular networks and 5G. In ATMS, the centralized approach to detect congestion and calculate alternative routes is one of the most adopted because of the difficulty of selecting the most appropriate vehicles in highly dynamic networks. The advantage of this approach is that it takes into consideration the scenario to its full extent at every execution. On the other hand, the distributed solution needs to previously segment the entire scenario to select the vehicles. Additionally, such solutions suggest alternative routes in a selfish fashion, which can lead to secondary congestions. These open issues have inspired the proposal of a distributed system of urban mobility management based on a collaborative approach in vehicular social networks (VSNs), named SOPHIA. The VSN paradigm has emerged from the integration of mobile communication devices and their social relationships in the vehicular environment. Therefore, social network analysis (SNA) and social network concepts (SNC) are two approaches that can be explored in VSNs. Our proposed solution adopts both SNA and SNC approaches for alternative route-planning in a collaborative way. Additionally, we used dynamic clustering to select the most appropriate vehicles in a distributed manner. Simulation results confirmed that the combined use of SNA, SNC, and dynamic clustering, in the vehicular environment, have great potential in increasing system scalability as well as improving urban mobility management efficiency1916CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQCOORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIOR - CAPESFUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO - FAPESP401802/2016-7; 2015/25588-6; 2016/24454-9; 2018/02204-6; 465446/2014-088887.136422/2017-002014/50937-

A Scalable Low-Cost-UAV Traffic Network (uNet)

This article proposes a new Unmanned Aerial Vehicle (UAV) operation paradigm to enable a large number of relatively low-cost UAVs to fly beyond-line-of-sight without costly sensing and communication systems or substantial human intervention in individual UAV control. Under current free-flight-like paradigm, wherein a UAV can travel along any route as long as it avoids restricted airspace and altitudes. However, this requires expensive on-board sensing and communication as well as substantial human effort in order to ensure avoidance of obstacles and collisions. The increased cost serves as an impediment to the emergence and development of broader UAV applications. The main contribution of this work is to propose the use of pre-established route network for UAV traffic management, which allows: (i) pre- mapping of obstacles along the route network to reduce the onboard sensing requirements and the associated costs for avoiding such obstacles; and (ii) use of well-developed routing algorithms to select UAV schedules that avoid conflicts. Available GPS-based navigation can be used to fly the UAV along the selected route and time schedule with relatively low added cost, which therefore, reduces the barrier to entry into new UAV-applications market. Finally, this article proposes a new decoupling scheme for conflict-free transitions between edges of the route network at each node of the route network to reduce potential conflicts between UAVs and ensuing delays. A simulation example is used to illustrate the proposed uNet approach.Comment: To be submitted to journal, 21 pages, 9 figure

Cooperative Perception for Social Driving in Connected Vehicle Traffic

The development of autonomous vehicle technology has moved to the center of automotive research in recent decades. In the foreseeable future, road vehicles at all levels of automation and connectivity will be required to operate safely in a hybrid traffic where human operated vehicles (HOVs) and fully and semi-autonomous vehicles (AVs) coexist. Having an accurate and reliable perception of the road is an important requirement for achieving this objective. This dissertation addresses some of the associated challenges via developing a human-like social driver model and devising a decentralized cooperative perception framework. A human-like driver model can aid the development of AVs by building an understanding of interactions among human drivers and AVs in a hybrid traffic, therefore facilitating an efficient and safe integration. The presented social driver model categorizes and defines the driver\u27s psychological decision factors in mathematical representations (target force, object force, and lane force). A model predictive control (MPC) is then employed for the motion planning by evaluating the prevailing social forces and considering the kinematics of the controlled vehicle as well as other operating constraints to ensure a safe maneuver in a way that mimics the predictive nature of the human driver\u27s decision making process. A hierarchical model predictive control structure is also proposed, where an additional upper level controller aggregates the social forces over a longer prediction horizon upon the availability of an extended perception of the upcoming traffic via vehicular networking. Based on the prediction of the upper level controller, a sequence of reference lanes is passed to a lower level controller to track while avoiding local obstacles. This hierarchical scheme helps reduce unnecessary lane changes resulting in smoother maneuvers. The dynamic vehicular communication environment requires a robust framework that must consistently evaluate and exploit the set of communicated information for the purpose of improving the perception of a participating vehicle beyond the limitations. This dissertation presents a decentralized cooperative perception framework that considers uncertainties in traffic measurements and allows scalability (for various settings of traffic density, participation rate, etc.). The framework utilizes a Bhattacharyya distance filter (BDF) for data association and a fast covariance intersection fusion scheme (FCI) for the data fusion processes. The conservatism of the covariance intersection fusion scheme is investigated in comparison to the traditional Kalman filter (KF), and two different fusion architectures: sensor-to-sensor and sensor-to-system track fusion are evaluated. The performance of the overall proposed framework is demonstrated via Monte Carlo simulations with a set of empirical communications models and traffic microsimulations where each connected vehicle asynchronously broadcasts its local perception consisting of estimates of the motion states of self and neighboring vehicles along with the corresponding uncertainty measures of the estimates. The evaluated framework includes a vehicle-to-vehicle (V2V) communication model that considers intermittent communications as well as a model that takes into account dynamic changes in an individual vehicle’s sensors’ FoV in accordance with the prevailing traffic conditions. The results show the presence of optimality in participation rate, where increasing participation rate beyond a certain level adversely affects the delay in packet delivery and the computational complexity in data association and fusion processes increase without a significant improvement in the achieved accuracy via the cooperative perception. In a highly dense traffic environment, the vehicular network can often be congested leading to limited bandwidth availability at high participation rates of the connected vehicles in the cooperative perception scheme. To alleviate the bandwidth utilization issues, an information-value discriminating networking scheme is proposed, where each sender broadcasts selectively chosen perception data based on the novelty-value of information. The potential benefits of these approaches include, but are not limited to, the reduction of bandwidth bottle-necking and the minimization of the computational cost of data association and fusion post processing of the shared perception data at receiving nodes. It is argued that the proposed information-value discriminating communication scheme can alleviate these adverse effects without sacrificing the fidelity of the perception

Roteamento de tráfego veicular colaborativo e sem infraestrutura para sistemas de transportes inteligentes

Orientadores: Leandro Aparecido Villas, Edmundo Roberto Mauro MadeiraTese (doutorado) - Universidade Estadual de Campinas, Instituto de ComputaçãoResumo: Devido à atual tendência mundial de urbanização, a sociedade moderna enfrenta, cada vez mais, sérios problemas de mobilidade urbana. Além disso, com o aumento constante do fluxo de tráfego veicular, as atuais soluções existentes para gerenciamento de tráfego se tornaram ineficientes. Com isso, para atender às crescentes necessidades dos sistemas de transporte, é necessário sistemas de transporte inteligentes (ITS). O desenvolvimento de ITS sustentável requer integração e interoperabilidade contínuas com tecnologias emergentes, tais como as redes veiculares (VANETs). As VANETs são consideradas uma tecnologia promissora que provê aplicações críticas de segurança e serviços de entretenimento, consequentemente melhorando a experiência de viagem do motorista e dos passageiros. Esta tese propõe um sistema de gerenciamento de tráfego de veículos sem a necessidade de uma infraestrutura de apoio. Para alcançar o sistema desejado foram necessários propor soluções intermediárias que contribuíram nesta tese. A primeira contribuição reside em uma solução que emprega conhecimento histórico dos padrões de mobilidade dos motoristas para obter uma visão global da situação da rede viária. Diferentemente de outras abordagens que precisam de troca constante de informações entre os veículos e o servidor central, nossa solução utiliza informações espaciais e temporais sobre padrões de mobilidade, além das informações específicas da infraestrutura viária, a fim de identificar congestionamentos no tráfego, permitindo, assim, o planejamento de roteamento de veículos. Como segunda contribuição, foi proposta uma solução distribuída para calcular a intermediação egocêntrica nas VANETs. Por meio da métrica egocêntrica foi proposto um mecanismo inovador de ranqueamento de veículos em redes altamente dinâmicas. As principais vantagens desse mecanismo para aplicações de VANETs são: (i) a redução do consumo de largura de banda e (ii) a superação do problema de topologias altamente dinâmicas. A terceira contribuição é uma solução de planejamento de rotas colaborativo com intuito de melhorar o gerenciamento do tráfego de veículos em cenários urbanos. Como última contribuição, esta tese integra as soluções descritas acima, propondo um sistema eficiente de gerenciamento de tráfego de veículos. As soluções propostas foram amplamente comparadas com outras soluções da literatura em diferentes métricas de avaliação de desempenho. Os resultados mostram que o sistema de gerenciamento de tráfego de veículos proposto é eficiente e escalável, qual pode ser uma boa alternativa para mitigar os problemas de mobilidade urbanaAbstract: Due to the current global trend of urbanization, modern society is facing severe urban mobility problems. In addition, considering the constant increase in vehicular traffic on roads, existing traffic management solutions have become inefficient. In order to assist the increasing needs of transport systems today, there is a need for intelligent transportation systems (ITS). Developing a sustainable ITS requires seamless integration and interoperability with emerging technologies such as vehicular ad-hoc networks (VANETs). VANETs are considered to be a promising technology providing access to critical life-safety applications and infotainment services, consequently improving drivers¿ and passengers¿ on-road experiences. This thesis proposes an infrastructure-less vehicular traffic management system. To achieve such a system, intermediate solutions that contributed to this thesis were proposed. The first contribution lies in a solution that employs historical knowledge of driver mobility patterns to gain an overall view of the road network situation. Unlike other approaches that need constant information exchange between vehicles and the central server, our solution uses space and temporal information about mobility patterns, as well as road infrastructure information, in order to identify traffic congestion, thus allowing for vehicle routing planning. Secondly, a distributed solution to calculate egocentric betweenness in VANETs was proposed. Through the egocentric metric, an innovative vehicle ranking mechanism in highly dynamic networks was proposed. The main advantages of this mechanism for VANETs applications are (i) reduced bandwidth consumption and (ii) overcoming the problem of highly dynamic topologies. The third contribution is a collaborative route planning solution designed to improve vehicle traffic management in urban settings. As the last contribution, this thesis integrates the solutions described above, proposing an efficient vehicle traffic management system. The proposed solutions were widely compared with other literature solutions on different performance evaluation metrics. The evaluation results show that the proposed vehicle traffic management system is efficient, scalable, and cost-effective, which may be a good alternative to mitigate urban mobility problemsDoutoradoCiência da ComputaçãoDoutor em Ciência da Computação2015/25588-6FAPES

Fast reroute using segment routing for smart grids

Tese de mestrado, Engenharia Informática (Arquitectura, Sistemas e Redes de Computadores) Universidade de Lisboa, Faculdade de Ciências, 2016A rede eléctrica tem contribuído de forma extraordinária para o nosso dia-a-dia nas últimas décadas e, como tal, tornou-se essencial para a nossa sociedade. Hoje em dia, estão a ser tomadas decisões para a modernizar, de modo a que seja possível fornecer novos serviços. Graças ao aumento da produção¸ ão de electricidade através de energias renováveis (energia solar, hídrica e eólica), e ao aumento do consumo de energia, é vista como necessária uma reestruturação da rede eléctrica. Para atingir estes objectivos, foi proposta uma nova geração destas redes, as Smart Grids (SG). As SG são compostas por dispositivos electrónicos inteligentes, sensores com e sem fios e contadores inteligentes que necessitam de se coordenar para funcionarem correctamente. Como tal, é fundamental ter uma rede de comunicação moderna capaz de suportar estes desafios [1]. Um conjunto de propriedades de que se destacam a escalabilidade, disponibilidade e segurança, são fulcrais para o funcionamento das SG. Para as SG a infra-estrutura de comunicação tem um papel particularmente importante para que se possam cumprir estas necessidades. As tecnologias actuais baseadas em Internet Protocol (IP) e em Multiprotocol Layer Switching (MPLS) tˆem conseguido corresponder a estas necessidades. O protocolo IP é um dos alicerces para a comunicação mundial, enquanto que o MPLS tem sido adoptado pelas suas capacidades de engenharia de tráfego. No entanto, as redes de IP tradicionais são difíceis de gerir e tornam complicado o desenho de soluções que permitam utilização eficiente de recursos e que possibilitem comunicação resiliente. Por outro lado, o MPLS tem problemas de escalabilidade devido ao uso de protocolos complexos como o Resource Reservation Protocol with Traffic Engineering (RSVP-TE). As Software Defined Networks (SDN) promete resolver alguns dos problemas mencionados anteriormente, a partir do desacoplamento do plano de dados do plano de controlo, que passa a ser gerido por um controlador logicamente centralizado [2][3][4]. Deste modo, as aplicações que são executadas no controlador têm uma visão centralizada do estado da rede, o que facilita a procura de soluções de gestão de redes. No entanto, os operadores de SG poderão apresentar alguma relutância ao mover todos os seus elementos da rede para uma SDN. Felizmente, foi proposto recentemente um novo protocolo pela Internet Engineering Task Force (IETF) – Segment Routing (SR) [5] – que permite a centralização lógica oferecida por uma SDN num ambiente de uma rede MPLS. SR ´e muito semelhante ao MPLS, na medida em que utiliza segmentos que se comportam como etiquetas MPLS. A comutação de pacotes, baseada também nestas etiquetas, é gerida por comutadores que usam as mesmas acções do MPLS (push, pop e swap). No entanto, ao contrário do MPLS, o SR não necessita de protocolos complexos como o RSVP-TE, simplificando a gestão da rede. O SR utiliza uma forma de source routing, facilitadora da sua integração. Desta forma o SR pode ser integrado com os controladores SDN e outras aplicações. Para implementar SR, o controlador SDN apenas precisa de enviar uma lista ordenada de segmentos para o encaminhador que a insere no cabeçalho dos pacotes quando necessitarem de serem enviados. Isto torna possível a criação de uma solução mais simples e escalável para engenharia de tráfego. Nesta tese vamos explorar o uso de SR para avaliar a resiliencia da rede. O objectivo passa por desenhar e avaliar as soluções que forneçam reencaminhamento rápido após uma falha de uma ligação entre nós. Em particular, fornece a capacidade de realizar reencaminhamento rápido enquanto fornece uma grande percentagem de cobertura. Aproveitando as características das SDN e de SR, as nossas soluções permitem que o controlador pré compute os caminhos de backup necessários para instalar nos encaminhadores, mantendo o plano de dados em MPLS inalterado. A contribuição principal desta tese pode ser resumida em dois pontos: 1. Desenho de uma solução de reencaminhamento rápido em caso de faltas para Smart Grids, usando SR e SDN. 2. Fornecer uma avaliação exaustiva do algoritmo de modo a que se consiga compreender os seus benefícios e limitações. O algoritmo proposto utiliza vários comutadores que são utilizados como destinos intermédios, que garantem a entrega dos pacotes após a falha de uma ligação entre nós. Como tal, também propomos dois selectores de segmentos que fornecem reencaminhamento rápido mas com características diferentes. A primeira solução, Fast Segment Drop (FSD), selecciona um segmento próximo da origem do caminho em vez do segmento mais próximo do destino. Isto permite que os pacotes que atravessam a rede causem o menor overhead possível. O overhead devese ao número de segmentos usados em cada nó durante o caminho. Assim sendo, se escolhermos um segmento mais próximo do destino o overhead será maior. A segunda solução, Congestion Avoidance Segment (CAS), escolhe segmentos que podem aumentar o overhead mas que, em contraste, fornecem a capacidade de escolher o caminho com menor utilização. Deste modo pode-se evitar estrangulamentos existentes na rede. Para compararmos as nossas soluções implementamos um selector aleatório e o algoritmo TI-LFA [6]. Os resultados demonstram que para a maioria das topologias uma falha entre nós pode ser tolerada utilizando Loop Free Alternatives (LFA). No entanto ainda existem cerca de 20% dos casos que necessitam de utilizar um segmento para tolerar uma falha, enquanto que dois segmentos raramente são necessários. Também foi possível concluir que o nosso algoritmo fornece mais flexibilidade na escolha de segmentos do que TI-LFA visto que permite uma maior escolha de segmentos. Utilizando CAS é possível reduzir ligeiramente a congestão das ligações na rede em grids e em topologias reais.With the increase of power generation from renewable sources and with a growing energy demand, the traditional communication network underpinning the actual electric power grid needs an overhaul. As a response, the Smart Grid is a new generation of electric grids that aims to fulfill this goal. Smart Grids demand a set of properties that range from high availability to scalability and security. Therefore, the communication infrastructure plays an important role. Current Internet Protocol-based and Multiprotocol Layer Switching (MPLS) technologies have been suggested capable in achieving those needs. However, IP networks have problems to offer traffic engineering solutions and MPLS faces scalability problems due to the use of complex protocols such as RSVP-TE. A new network paradigm, Software-Defined Networks (SDN), is revolutionizing the way computer networks are built and operated, and is leading to the “softwarization” of networking. Showing promise to solve some of the above problems. However, smart grid operators may be reluctant to move all their network elements to SDN anytime soon. Fortunately, Segment routing, recently proposed by the IETF, allows SDN to be used in the context of MPLS networks. The data plane of Segment Routing is similar to MPLS as it uses segments that behave as MPLS labels and is managed in switches using similar actions. In this thesis we present algorithms for fast reroute in SR networks. We propose two solutions: Fast Segment Drop (FSD) that aims to minimize packet overhead and segment list size; and Congestion Avoidance Segment (CAS), a solution that provides traffic engineering by minimizing the maximum link load. The results indeed show that by using CAS reduces network congestion when compared with other algorithms. FSD provides higher coverage using just one segment thus reducing overhead

CONGESTION CONTROL FOR A ULTRA-WIDEBAND DYNAMIC SENSOR NETWORK USING AUTONOMIC BASED LEARNING

The physical conditions of the area of interest is being collected at the central location using a set of dedicated sensors that forms a network is referred to as Wireless Sensor Network. A dynamic environment is required for a secure multi-hop communication between nodes of the heterogeneous Wireless Sensor Network. One such solution is to employ autonomic based learning in a MAC Layer of the UWB TxRx. Over a time period the autonomic based network learns from the previous experience and adapts to the environment significantly. Exploring the Autonomicity would help us in evading the congestion of about 30% in a typical UWB-WSNs. Simulation results showed an improvement of 5% using Local Automate Collision Avoidance Scheme (LACAS-UWB) compared to LACAS

Resilient and Scalable Forwarding for Software-Defined Networks with P4-Programmable Switches

Traditional networking devices support only fixed features and limited configurability. Network softwarization leverages programmable software and hardware platforms to remove those limitations. In this context the concept of programmable data planes allows directly to program the packet processing pipeline of networking devices and create custom control plane algorithms. This flexibility enables the design of novel networking mechanisms where the status quo struggles to meet high demands of next-generation networks like 5G, Internet of Things, cloud computing, and industry 4.0. P4 is the most popular technology to implement programmable data planes. However, programmable data planes, and in particular, the P4 technology, emerged only recently. Thus, P4 support for some well-established networking concepts is still lacking and several issues remain unsolved due to the different characteristics of programmable data planes in comparison to traditional networking. The research of this thesis focuses on two open issues of programmable data planes. First, it develops resilient and efficient forwarding mechanisms for the P4 data plane as there are no satisfying state of the art best practices yet. Second, it enables BIER in high-performance P4 data planes. BIER is a novel, scalable, and efficient transport mechanism for IP multicast traffic which has only very limited support of high-performance forwarding platforms yet. The main results of this thesis are published as 8 peer-reviewed and one post-publication peer-reviewed publication. The results cover the development of suitable resilience mechanisms for P4 data planes, the development and implementation of resilient BIER forwarding in P4, and the extensive evaluations of all developed and implemented mechanisms. Furthermore, the results contain a comprehensive P4 literature study. Two more peer-reviewed papers contain additional content that is not directly related to the main results. They implement congestion avoidance mechanisms in P4 and develop a scheduling concept to find cost-optimized load schedules based on day-ahead forecasts