A Novel Approach for Image Localization Using SVM Classifier and PSO Algorithm for Vehicle Tracking

In this paper, we propose a novel methodology for vehicular image localization, by incorporating the surveillance image object identification, using a local gradient model, and vehicle localization using the time of action. The aerial images of different traffic densities are obtained using the Histograms of Oriented Gradients (HOG) Descriptor. These features are acquired simply based on locations, angles, positions, and height of cameras set on the junction board. The localization of vehicular image is obtained based on the different times of action of the vehicles under consideration. Support Vector Machines (SVM) classifier, as well as Particle Swarm Optimization (PSO), is also proposed in this work. Different experimental analyses are also performed to calculate the efficiency of optimization methods in the new proposed system. Outcomes from experimentations reveal the effectiveness of the classification precision, recall, and F measure

Cooperative & cost-effective network selection: a novel approach to support location-dependent & context-aware service migration in VANETs

Vehicular networking has gained considerable interest within the research community and industry. This class of mobile ad hoc network expects to play a vital role in the design and deployment of intelligent transportation systems. The research community expects to launch several innovative applications over Vehicular Ad hoc Networks (VANETs). The automotive industry is supporting the notion of pervasive connectivity by agreeing to equip vehicles with devices required for vehicular ad hoc networking. Equipped with these devices, mobile nodes in VANETs are capable of hosting many types of applications as services for other nodes in the network. These applications or services are classified as safety-critical (failure or unavailability of which may lead to a life threat) and non-safety-critical (failure of which do not lead to a life threat). Safety-critical and non-safety-critical applications need to be supported concurrently within VANETs. This research covers non-safety-critical applications since the research community has overlooked this class of applications. More specifically, this research focuses on VANETs services that are location-dependent. Due to high speed mobility, VANETs are prone to intermittent network connectivity. It is therefore envisioned that location-dependence and intermittent network connectivity are the two major challenges for VANETs to host and operate non-safety-critical VANETs services. The challenges are further exacerbated when the area where the services are to be deployed is unplanned i.e. lacks communication infrastructure and planning. Unplanned areas show irregular vehicular traffic on the road. Either network traffic flows produced by irregular vehicular traffic may lead to VANETs communication channel congestion, or it may leave the communication channel under-utilized. In both cases, this leads to communication bottlenecks within VANETs. This dissertation investigates the shortcomings of location-dependence, intermittent network connectivity and irregular network traffic flows and addresses them by exploiting location-dependent service migration over an integrated network in an efficient and cost-effective manner

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

Trajectory Privacy Preservation and Lightweight Blockchain Techniques for Mobility-Centric IoT

Various research efforts have been undertaken to solve the problem of trajectory privacy preservation in the Internet of Things (IoT) of resource-constrained mobile devices. Most attempts at resolving the problem have focused on the centralized model of IoT, which either impose high delay or fail against a privacy-invading attack with long-term trajectory observation. These proposed solutions also fail to guarantee location privacy for trajectories with both geo-tagged and non-geo-tagged data, since they are designed for geo-tagged trajectories only. While a few blockchain-based techniques have been suggested for preserving trajectory privacy in decentralized model of IoT, they require large storage capacity on resource-constrained devices and can only provide conditional privacy when a set of authorities governs the blockchain. This dissertation addresses these challenges to develop efficient trajectory privacy-preservation and lightweight blockchain techniques for mobility-centric IoT. We develop a pruning-based technique by quantifying the relationship between trajectory privacy and delay for real-time geo-tagged queries. This technique yields higher trajectory privacy with a reduced delay than contemporary techniques while preventing a long-term observation attack. We extend our study with the consideration of the presence of non-geo-tagged data in a trajectory. We design an attack model to show the spatiotemporal correlation between the geo-tagged and non-geo-tagged data which undermines the privacy guarantee of existing techniques. In response, we propose a methodology that considers the spatial distribution of the data in trajectory privacy-preservation and improves existing solutions, in privacy and usability. With respect to blockchain, we design and implement one of the first blockchain storage management techniques utilizing the mobility of the devices. This technique reduces the required storage space of a blockchain and makes it lightweight for resource-constrained mobile devices. To address the trajectory privacy challenges in an authority-based blockchain under the short-range communication constraints of the devices, we introduce a silence-based one of the first technique to establish a balance between trajectory privacy and blockchain utility. The designed trajectory privacy- preservation techniques we established are light- weight and do not require an intermediary to guarantee trajectory privacy, thereby providing practical and efficient solution for different mobility-centric IoT, such as mobile crowdsensing and Internet of Vehicles

Mobility-aware Software-Defined Service-Centric Networking for Service Provisioning in Urban Environments

Disruptive applications for mobile devices, such as the Internet of Things, Connected and Autonomous Vehicles, Immersive Media, and others, have requirements that the current Cloud Computing paradigm cannot meet. These unmet requirements bring the necessity to deploy geographically distributed computing architectures, such as Fog and Mobile Edge Computing. However, bringing computing close to users has its costs. One example of cost is the complexity introduced by the management of the mobility of the devices at the edge. This mobility may lead to issues, such as interruption of the communication with service instances hosted at the edge or an increase in communication latency during mobility events, e.g., handover. These issues, caused by the lack of mobility-aware service management solutions, result in degradation in service provisioning. The present thesis proposes a series of protocols and algorithms to handle user and service mobility at the edge of the network. User mobility is characterized when user change access points of wireless networks, while service mobility happens when services have to be provisioned from different hosts. It assembles them in a solution for mobility-aware service orchestration based on Information-Centric Networking (ICN) and runs on top of Software-Defined Networking (SDN). This solution addresses three issues related to handling user mobility at the edge: (i) proactive support for user mobility events, (ii) service instance addressing management, and (iii) distributed application state data management. For (i), we propose a proactive SDN-based handover scheme. For (ii), we propose an ICN addressing strategy to remove the necessity of updating addresses after service mobility events. For (iii), we propose a graph-based framework for state data placement in the network nodes that accounts for user mobility and latency requirements. The protocols and algorithms proposed in this thesis were compared with different approaches from the literature through simulation. Our results show that the proposed solution can reduce service interruption and latency in the presence of user and service mobility events while maintaining reasonable overhead costs regarding control messages sent in the network by the SDN controller

Security of Cyber-Physical Systems

Cyber-physical system (CPS) innovations, in conjunction with their sibling computational and technological advancements, have positively impacted our society, leading to the establishment of new horizons of service excellence in a variety of applicational fields. With the rapid increase in the application of CPSs in safety-critical infrastructures, their safety and security are the top priorities of next-generation designs. The extent of potential consequences of CPS insecurity is large enough to ensure that CPS security is one of the core elements of the CPS research agenda. Faults, failures, and cyber-physical attacks lead to variations in the dynamics of CPSs and cause the instability and malfunction of normal operations. This reprint discusses the existing vulnerabilities and focuses on detection, prevention, and compensation techniques to improve the security of safety-critical systems

Feature Papers of Drones - Volume I

[EN] The present book is divided into two volumes (Volume I: articles 1–23, and Volume II: articles 24–54) which compile the articles and communications submitted to the Topical Collection ”Feature Papers of Drones” during the years 2020 to 2022 describing novel or new cutting-edge designs, developments, and/or applications of unmanned vehicles (drones). Articles 1–8 are devoted to the developments of drone design, where new concepts and modeling strategies as well as effective designs that improve drone stability and autonomy are introduced. Articles 9–16 focus on the communication aspects of drones as effective strategies for smooth deployment and efficient functioning are required. Therefore, several developments that aim to optimize performance and security are presented. In this regard, one of the most directly related topics is drone swarms, not only in terms of communication but also human-swarm interaction and their applications for science missions, surveillance, and disaster rescue operations. To conclude with the volume I related to drone improvements, articles 17–23 discusses the advancements associated with autonomous navigation, obstacle avoidance, and enhanced flight plannin

A Pattern-Based Approach to Scaffold the IT Infrastructure Design Process

Context. The design of Information Technology (IT) infrastructures is a challenging task since it implies proficiency in several areas that are rarely mastered by a single person, thus raising communication problems among those in charge of conceiving, deploying, operating and maintaining/managing them. Most IT infrastructure designs are based on proprietary models, known as blueprints or product-oriented architectures, defined by vendors to facilitate the configuration of a particular solution, based upon their services and products portfolio. Existing blueprints can be facilitators in the design of solutions for a particular vendor or technology. However, since organizations may have infrastructure components from multiple vendors, the use of blueprints aligned with commercial product(s) may cause integration problems among these components and can lead to vendor lock-in. Additionally, these blueprints have a short lifecycle, due to their association with product version(s) or a specific technology, which hampers their usage as a tool for the reuse of IT infrastructure knowledge. Objectives. The objectives of this dissertation are (i) to mitigate the inability to reuse knowledge in terms of best practices in the design of IT infrastructures and, (ii) to simplify the usage of this knowledge, making the IT infrastructure designs simpler, quicker and better documented, while facilitating the integration of components from different vendors and minimizing the communication problems between teams. Method. We conducted an online survey and performed a systematic literature review to support the state of the art and to provide evidence that this research was relevant and had not been conducted before. A model-driven approach was also used for the formalization and empirical validation of well-formedness rules to enhance the overall process of designing IT infrastructures. To simplify and support the design process, a modeling tool, including its abstract and concrete syntaxes was also extended to include the main contributions of this dissertation. Results. We obtained 123 responses to the online survey. Their majority were from people with more than 15 years experience with IT infrastructures. The respondents confirmed our claims regarding the lack of formality and documentation problems on knowledge transfer and only 19% considered that their current practices to represent IT Infrastructures are efficient. A language for modeling IT Infrastructures including an abstract and concrete syntax is proposed to address the problem of informality in their design. A catalog of IT Infrastructure patterns is also proposed to allow expressing best practices in their design. The modeling tool was also evaluated and according to 84% of the respondents, this approach decreases the effort associated with IT infrastructure design and 89% considered that the use of a repository with infrastructure patterns, will help to improve the overall quality of IT infrastructures representations. A controlled experiment was also performed to assess the effectiveness of both the proposed language and the pattern-based IT infrastructure design process supported by the tool. Conclusion. With this work, we contribute to improve the current state of the art in the design of IT infrastructures replacing the ad-hoc methods with more formal ones to address the problems of ambiguity, traceability and documentation, among others, that characterize most of IT infrastructure representations. Categories and Subject Descriptors:C.0 [Computer Systems Organization]: System architecture; D.2.10 [Software Engineering]: Design-Methodologies; D.2.11 [Software Engineering]: Software Architectures-Patterns

Long-term tracking and monitoring of mobile entities in the outdoors using wireless sensors

There is an emerging class of applications that require long-term tracking and monitoring of mobile entities for characterising their contexts and behaviours using data from wireless sensors. Examples include monitoring animals in their natural habitat over the annual cycle; tracking shipping containers and their handling during transit; and monitoring air quality using sensors attached to bicycles used in public sharing schemes. All applications within this class require the acquisition of sensor data tagged with spatio-temporal information and uploaded wirelessly. Currently there is no solution targeting the entire class of applications, only point solutions focused on specific scenarios. This thesis presents a complete solution (firmware and hardware) for applications within this class that consists of attaching mobile sensor nodes to the entities for tracking and monitoring their behaviour, and deploying an infrastructure of base-stations for collecting the data wirelessly. The proposed solution is more energy efficient compared to the existing solutions that target specific scenarios, offering a longer deployment lifetime with a reduced size and weight of the devices. This is achieved mainly by using the VB-TDMA low-power data upload protocol proposed in this thesis. The mobile sensor nodes, consisting of the GPS and radio modules among others, and the base-stations are powered by batteries, and the optimisation of their energy usage is of primary concern. The presence of the GPS module, in particular its acquisition of accurate time, is used by the VB-TDMA protocol to synchronise the communication between nodes at no additional energy costs, resulting in an energy-efficient data upload protocol for sparse networks of mobile nodes, that can potentially be out of range of base-stations for extended periods of time. The VB-TDMA and an asynchronous data upload protocol were implemented on the custom-designed Prospeckz-5-based wireless sensor nodes. The protocols’ performances were simulated in the SpeckSim simulator and validated in real-world deployments of tracking and monitoring thirty-two Retuerta wild horses in the Doñana National Park in Spain, and a herd of domesticated horses in Edinburgh. The chosen test scenario of long-term wildlife tracking and monitoring is representative for the targeted class of applications. The VB-TDMA protocol showed a significantly lower power consumption than other comparable MAC protocols, effectively doubling the battery lifetime. The main contributions of the thesis are the development of the VB-TDMA data upload protocol and its performance evaluation, along with the development of simulation models for performance analysis of wireless sensor networks, validated using data from the two real-world deployments