General queuing model for optimal seamless delivery of payload processing in multi-core processors

This is a pre-print of an article published in The Journal of Supercomputing. The final authenticated version is available online at: https://doi.org/10.1007/s11227-017-2109-4.Recent developments in unmanned aerial systems (UAS) provide new opportunities in remote sensing application. In contrast to satellite and conventional (manned) aerial tasks, UAS flights can be operated in a very short period of time. UAS can also be more specifically focused toward a given task such as crop reconnaissance or electric line tower inspection. For some applications, the delivery time of the remote sensing results is crucial. The current three-phase procedure of data acquisition, data downloading and data processing, performed sequentially in time, represents a drawback that reduces the benefits of using unmanned aerial systems. In this paper, we present a parallel processing strategy, based on queuing theory, in which the data processing phase is performed on board in parallel with data acquisition. The unmanned aerial system payload has been enlarged with low-cost, lightweight, multi-core boards to facilitate remote sensing data processing during flight. The storage of the raw sensing data is also done for possible further analysis; however, the ultimate decision support information can be seamless delivered to the customer upon landing. Furthermore, text alarms and limited imagery can also be provided during flight.Peer ReviewedPostprint (author's final draft

Conducción social cooperativa en ciudades inteligentes

Most of the world population lives in urban areas, and it is expected that the number ofinhabitants in cities will be 75% of the world's population by 2050. Thus, a wide rangeof challenges have to be faced by the different city stakeholders in order to mitigate thenegative effects of a very fast growth of such urban areas. One of the main concerns inmodern cities is mobility. The vast increment in the volume of urban road trafficexperienced during the last decades causes serious issues that have be confrontedwith new tools. Traffic jams bother the daily life of the population, mainly because trafficcongestion causes longer trip times and a larger associated pollution, not to mentionthe economic losses due to delays and other transport problems. Thus, great effortsare being made to develop Smart Mobility solutions.Vehicular ad hoc networks (VANETs) are based on the spontaneous creation of awireless network for data exchange between vehicles, mainly. Wireless networkingtechnologies are used in VANETs, including short range radio and cellular. Thesecommunication networks are leading the automotive industry today, as they have led tothe emergence of the connected vehicle and the Social Cooperative Driving (CSD).CSD allow drivers and vehicles to access different data sources in order to increasethe knowledge about the current road traffic status. Besides, other types ofinfotainment services and applications can be deployed using VANETs.File transferring is always an essential service in VANETs since their ultimate purposeis the exchange of information among the nodes. Thus, it is desirable to optimize the file transferring protocol to provide the applications with the best service possible. Oneof the ways to get such an efficient protocols is to better fit their configurationparameters to the VANETs specifications. This study proposes the application ofComputational Intelligence to obtain automatically optimal protocol configurations forvehicular environments. The main idea is to define the protocol configuration as anoptimization problem and address it by using intelligent tools, such as metaheuristics,and a realistic simulation procedure to evaluate the obtained solutions.In this work, we have carried out a real world testbed at streets of Málaga in order tostudy the performance of the analyzed file transfer protocol by exchanging informationbetween cars in a real urban. These experiments have confirmed the efficiency ofconfiguring VANET nodes with protocols improved by applying our methodology.Uno de los mayores retos a los que se enfrentan las sociedades modernas es lamovilidad urbana. La congestión de las carreteras y los problemas de seguridad vialson considerados factores clave en la degradación de la calidad de vida de losciudadanos. Las innovaciones tecnológicas que consigan mejorar la movilidadmarcarán gran parte del futuro de las ciudades inteligentes. Una de las tecnologíasmás prometedoras aplicadas a este ámbito son las redes vehiculares ad hoc. Estasredes de comunicación inalámbrica permiten la comunicación directa, gratuita ydinámica entre vehículos cercanos y de estos con elementos de la infraestructura vial.Estas redes de comunicación están marcando la industria del automóvil actual, ya quehan propiciado el surgimiento del vehículo conectado y la Conducción SocialCooperativa (Cooperative Social Driving, CSD). El acceso a distintas fuentes deinformación permite ampliar enormemente las funcionalidades del vehículo. El CSDpermite que los vehículos cercanos puedan interactuar intercambiando informaciónrelevante en tiempo real. Esta información puede haber sido recogida por los sensoresdel vehículo, introducida por usuarios o recibida de otro vehículo. De este modo losconductores circulan con una percepción más completa del estado real del tráfico ypueden ser advertidos sobre la existencia de obstáculos, accidentes, peatones en lavía u otro cualquier hecho importante. También se pueden desarrollar utilidades, comocrear nubes para el intercambio de documentos, fotos, vídeos y juegos.El CSD se sustenta en el intercambio de archivos, siendo capital que la transferenciade los mismos sea óptima. El que un mensaje llegue y que lo haga a tiemporepresenta la diferencia de evitar o no una situación peligrosa. Nuestro grupo deinvestigación ha desarrollado protocolos para este fin, y ha optimizado los existentes para que comiencen a ser útiles en situaciones reales de velocidades variadas yvolatilidad de la conexión.Por lo general, son expertos quienes por su experiencia o llevando a caboexperimentos de laboratorio proponen la configuración de un protocolo. En el presenteartículo se presenta la aplicación de la Inteligencia Computacional para laconfiguración automática e inteligente de protocolos aplicados en redes vehiculares.Para ello se ha definido la configuración de protocolos como un problema deoptimización y se han diseñado algoritmos inspirados en la naturaleza para resolverlo.Entre los algoritmos empleados destacan los Algoritmos Genéticos, que se basan enla Teoría de Darwin de la evolución de las especies, y los algoritmos de Optimizaciónpor Cúmulo de Partículas, inspirados en el comportamiento social de los animalescomo las aves en una bandada.Estos algoritmos se han combinado con un simulador de redes vehiculares realista yde forma automática han calculado configuraciones óptimas que han mejoradoconsiderablemente el rendimiento de los protocolos de comunicación analizados. Enlas pruebas reales en ciudad (Málaga), sólo los protocolos optimizados empleandonuestra metodología han podido transmitir la información que se requería de unvehículo a otro. Las aplicaciones posibles son innumerables, y la tecnología está listapara generar productos que se acepten en el mercado actual

Improving the Routing Layer of Ad Hoc Networks Through Prediction Techniques

Cada dia és més evident el paper clau que juguen la informàtica/computació mòbil i les tecnologies sense fils a les nostres activitats diàries. Estar sempre connectat, en qualsevol moment i lloc, és actualment més una necessitat que un luxe. Els escenaris de computació ubics creats en base a aquests avenços tecnològics, permeten a les persones proporcionar i consumir informació compartida. En aquests escenaris, les xarxes que donen suport a aquestes comunicacions són típicament sense fils i ad hoc. Les característiques dinàmiques i canviants de les xarxes ad hoc, fan que el treball realitzat per la capa d'enrutament tingui un gran impacte en el rendiment d'aquestes xarxes. És molt important que la capa d'enrutament reaccioni ràpidament als canvis que es produeixen, i fins i tot s'avanci als que es produiran en un futur proper, mitjançant l'aplicació de tècniques de predicció. Aquesta tesi investiga si les tècniques de predicció poden millorar la capa d'enrutament de les xarxes ad hoc. Com a primer pas en aquesta direcció, explorem la potencialitat d'una estratègia de Predictor-Basat-en-Història (HBP) per predir la Informació de Control Topològic (TCI) generada pels protocols d'enrutament. Demostrem que hi ha una gran oportunitat per predir TCI, i aquesta predicció pot centrar-se en un petit subconjunt de missatges. En base a les nostres troballes, implementem el predictor OLSR-HBP i l'avaluem respecte al protocol Optimized Link State Routing (OLSR). OLSR-HBP aconsegueix disminucions importants de TCI (sobrecàrrega de senyalització), sense afectar el funcionament de la xarxa i necessita una quantitat de recursos petita i assequible. Finalment, en referència a l'impacte de la predicció en les dades d'enrutament tant de la informació de Qualitat d'Enllaç como de Ruta (o Extrem-a-Extrem), demostrem que l'Anàlisi de Sèries Temporals és un enfocament prometedor per predir amb precisió, tant la Qualitat d'Enllaç como la Qualitat d'Extrem a Extrem en Xarxes Comunitàries.Cada día es más evidente el papel clave que juegan la informática/computación móvil y las tecnologías inalámbricas en nuestras actividades diarias. Estar siempre conectado, en cualquier momento y lugar, es actualmente más una necesidad que un lujo. Los escenarios de computación ubicuos creados en base a estos avances tecnológicos, permiten a las personas proporcionar y consumir información compartida. En estos escenarios, las redes que dan soporte a estas comunicaciones son típicamente inalámbricas y ad hoc. Las características dinámicas y cambiantes de las redes ad hoc, hacen que el trabajo realizado por la capa de enrutamiento tenga un gran impacto en el rendimiento de estas redes. Es muy importante que la capa de enrutamiento reaccione rápidamente a los cambios que se producen, e incluso se adelante a los que sucederán en un futuro cercano, mediante la aplicación de técnicas de predicción. Esta tesis investiga si las técnicas de predicción pueden mejorar la capa de enrutamiento de las redes ad hoc. Como primer paso en esta dirección, exploramos la potencialidad de una estrategia de Predictor-Basado-en-Historia (HBP) para predecir la Información de Control Topológico (TCI) generada por los protocolos de enrutamiento. Demostramos que hay una gran oportunidad para predecir TCI, y esta predicción puede centrarse en un pequeño subconjunto de mensajes. En base a nuestros hallazgos, implementamos el predictor OLSR-HBP y lo evaluamos con respecto al protocolo Optimized Link State Routing (OLSR). OLSR-HBP consigue disminuciones importantes de TCI (sobrecarga de señalización), sin afectar al funcionamiento de la red, y necesita una cantidad de recursos pequeña y asequible. Finalmente, en referencia al impacto de la predicción en los datos de enrutamiento tanto de la información de Calidad de Enlace como de Ruta (o Extremo-a-Extremo), demostramos que el Análisis de Series Temporales es un enfoque prometedor para predecir con precisión, tanto la Calidad de Enlace como la Calidad de Extremo a Extremo en Redes Comunitarias.Everyday becomes more evident the key role that mobile computing and wireless technologies play in our daily activities. Being always connected, anytime, and anywhere is today more a necessity than a luxury. The ubiquitous computing scenarios created based on these technology advances allow people to provide and consume shared information. In these scenarios, the supporting communication networks are typically wireless and ad hoc. The dynamic and changing characteristics of the ad hoc networks, makes the work done by the routing layer to have a high impact on the performance of these networks. It is very important for the routing layer to quickly react to changes that happen, and even be advanced to what will happen in the near future, by applying prediction techniques. This thesis investigates whether prediction techniques can improve the routing layer of ad hoc networks. As a first step in this direction, in this thesis we explored the potentiality of a History-Based Predictor (HBP) strategy to predict the Topology Control Information (TCI) generated by routing protocols. We demonstrated that there is a high opportunity for predicting theTCI, and this prediction can be just focused on a small subset of messages. Based on our findings we implemented the OLSR-HBP predictor and evaluated it with regard to the Optimized Link State Routing (OLSR) protocol. OLSR History-Based Predictor (OLSR-HBP) achieved important decreases of TCI (signaling overhead), without disturbing the network operation, and requiring a small and affordable amount of resources. Finally, regarding the impact of Prediction on the routing data for both Link and Path (or End-to-End) Quality information, we demonstrated that Time-series analysis is a promising approach to accurately predict both Link and End-to-End Quality in Community Networks

The Digital Transformation of Automotive Businesses: THREE ARTEFACTS TO SUPPORT DIGITAL SERVICE PROVISION AND INNOVATION

Digitalisation and increasing competitive pressure drive original equipment manufacturers (OEMs) to switch their focus towards the provision of digital services and open-up towards increased collaboration and customer integration. This shift implies a significant transformational change from product to product-service providers, where OEMs realign themselves within strategic, business and procedural dimensions. Thus, OEMs must manage digital transformation (DT) processes in order to stay competitive and remain adaptable to changing customer demands. However, OEMs aspiring to become participants or leaders in their domain, struggle to initiate activities as there is a lack of applicable instruments that can guide and support them during this process. Compared to the practical importance of DT, empirical studies are not comprehensive. This study proposes three artefacts, validated within case companies that intend to support automotive OEMs in digital service provisioning. Artefact one, a layered conceptual model for a digital automotive ecosystem, was developed by means of 26 expert interviews. It can serve as a useful instrument for decision makers to strategically plan and outline digital ecosystems. Artefact two is a conceptual reference framework for automotive service systems. The artefact was developed based on an extensive literature review, and the mapping of the business model canvas to the service system domain. The artefact intends to assist OEMs in the efficient conception of digital services under consideration of relevant stakeholders and the necessary infrastructures. Finally, artefact three proposes a methodology by which to transform software readiness assessment processes to fit into the agile software development approach with consideration of the existing operational infrastructure. Overall, the findings contribute to the empirical body of knowledge about the digital transformation of manufacturing industries. The results suggest value creation for digital automotive services occurs in networks among interdependent stakeholders in which customers play an integral role during the services’ life-cycle. The findings further indicate the artefacts as being useful instruments, however, success is dependent on the integration and collaboration of all contributing departments.:Table of Contents Bibliographic Description II Acknowledgment III Table of Contents IV List of Figures VI List of Tables VII List of Abbreviations VIII 1 Introduction 1 1.1 Motivation and Problem Statement 1 1.2 Objective and Research Questions 6 1.3 Research Methodology 7 1.4 Contributions 10 1.5 Outline 12 2 Background 13 2.1 From Interdependent Value Creation to Digital Ecosystems 13 2.1.1 Digitalisation Drives Collaboration 13 2.1.2 Pursuing an Ecosystem Strategy 13 2.1.3 Research Gaps and Strategy Formulation Obstacles 20 2.2 From Products to Product-Service Solutions 22 2.2.1 Digital Service Fulfilment Requires Co-Creational Networks 22 2.2.2 Enhancing Business Models with Digital Services 28 2.2.3 Research Gaps and Service Conception Obstacles 30 2.3 From Linear Development to Continuous Innovation 32 2.3.1 Digital Innovation Demands Digital Transformation 32 2.3.2 Assessing Digital Products 36 2.3.3 Research Gaps and Implementation Obstacles 38 3 Artefact 1: Digital Automotive Ecosystems 41 3.1 Meta Data 41 3.2 Summary 42 3.3 Designing a Layered Conceptual Model of a Digital Ecosystem 45 4 Artefact 2: Conceptual Reference Framework 79 4.1 Meta Data 79 4.2 Summary 80 4.3 On the Move Towards Customer-Centric Automotive Business Models 83 5 Artefact 3: Agile Software Readiness Assessment Procedures 121 5.1 Meta Data 121 5.2 Meta Data 122 5.3 Summary 123 5.4 Adding Agility to Software Readiness Assessment Procedures 126 5.5 Continuous Software Readiness Assessments for Agile Development 147 6 Conclusion and Future Work 158 6.1 Contributions 158 6.1.1 Strategic Dimension: Artefact 1 158 6.1.2 Business Dimension: Artefact 2 159 6.1.3 Process Dimension: Artefact 3 161 6.1.4 Synthesis of Contributions 163 6.2 Implications 167 6.2.1 Scientific Implications 167 6.2.2 Managerial Implications 168 6.2.3 Intelligent Parking Service Example (ParkSpotHelp) 171 6.3 Concluding Remarks 174 6.3.1 Threats to Validity 174 6.3.2 Outlook and Future Research Recommendations 174 Appendix VII Bibliography XX Wissenschaftlicher Werdegang XXXVII Selbständigkeitserklärung XXXVII

Estratégias para diminuição do tráfego de dados e controlo em mecanismos de disseminação de conteúdos em redes veiculares

Desde sempre que a conetividade assume um papel importante em manter as pessoas ligadas entre si e ao resto do mundo. Tal facto não mudou nos tempos atuais, especialmente na era das novas tecnologias, onde se tem assistido á introdução de novas redes de telecomunicações. Entre elas destacam-se as redes veiculares constituídas por todo o tipo de veículos com capacidades de intercomunicação. Estas redes veiculares fornecem diversos serviços, nos quais se destacam o acesso à Internet, coleta de dados sensoriais e a distribuição de conteúdos não urgentes. No entanto, as redes veiculares têm carateristicas especificas, face a outro tipo de redes, tais como, o número elevado de veículos, rotas imprevisiveis e a constante perda de conectividade entre os mesmos, relevando vários desafios a solucionar. A solução encontrada para a conectividade intermitente prende-se com o uso de Delay-Tolerant Network (DTN)s, cuja arquitetura assegura a entrega de informação mesmo quando não existe o conhecimento total do percurso que esta deve percorrer, desde a origem até ao destino. O trabalho realizado nesta dissertação foca-se na diminuição do tráfego de dados e controlo em mecanismos de disseminação de conteúdos não urgentes em redes veiculares. Atualmente, existem três estratégias já implementadas pelo grupo Network Architecture and Protocols (NAP) para distribuição de conteúdos não urgentes. Destas três, apenas uma delas se destaca, a estratégia LRBF, pela elevada taxa de entrega. No entanto, a elevada taxa de entrega força um overhead considerável na rede. Para combater este efeito, foram desenvolvidas quatro abordagens para diminuição do tráfego de controlo. Posteriormente a melhor abordagem (BitArray) foi escolhida para integrar numa nova estratégia, LRBFAdvanced. Para além disso, esta nova estratégia consistiu, também, num conjunto de otimizações efetuadas ao nível dos pacotes de dados da estratégia base, LRBF, para combater o número de pacotes de dados redundantes na rede. Tanto a nova estratégia como as abordagens desenvolvidas de diminuição de tráfego de controlo foram implementadas no software de DTNs mOVERS Emulator, e sempre avaliadas em relação à estratégia base. Posteriormente, a estratégia LRBFAdvanced, assim como a estratégia LRBF (para efeitos de comparação), foram introduzidas e testadas numa plataforma real (em ambiente controlado - laboratorial, e em ambiente não controlado - moliceiros na ria de Aveiro) para demonstrar que, de facto, o objetivo principal da LRBFAdvanced é cumprido e atingido na prática. Após análise dos resultados obtidos conclui-se que a nova estratégia resultante proposta, denominada LRBFAdvanced, cumpriu o principal objetivo proposto, nomeadamente, a redução do overhead na rede veicular, tanto de controlo como de dados.Connectivity is playing an important role in keeping people connected to each other and to the rest of the world. This has not changed in the actual time, especially in the field of new technologies, where new telecommunication networks have been introduced. These include vehicular networks made up of all types of vehicles with intercommunication capabilities. These vehicular networks provide a variety of services, that can be Internet access, sensor data collection and the distribution of non-urgent content. However, vehicular networks have specific characteristics when compared with other types of networks, such as the high number of vehicles, unpredictable routes and the constant loss of connectivity between them, highlighting several challenges to be solved. The solution found for intermittent connectivity concerns the use of DTNs, whose architecture ensures the delivery of information even when there is no complete knowledge of the route that it must travel, from the origin to the destination. The work carried out in this dissertation focuses on the reduction of data and control trafic in non-urgent content dissemination mechanisms in vehicular networks. Currently, there are three strategies already implemented by the NAP group for non-urgent content distribution. Of these three, only one of them stands out, the Local Rarest Bundle First (LRBF) strategy, achieving high rate of delivery. However, the high delivery rate forces a considerable overhead on the network. To overcome this drawback, four approaches have been developed to reduce control trafic. Subsequently the best approach (BitArray) was chosen to integrate into a new strategy, LRBFAdvanced. In addition, this new strategy also consisted of a set of optimizations made at the level of the base strategy data packets, LRBF, to overcome the excessive number of redundant data packets in the network. Both the new strategy and the developed control trafic reduction approaches were implemented in the mOVERS Emulator DTNs software, and always evaluated against the base strategy. Later, the LRBFAdvanced strategy, as well as the LRBF strategy (for comparison purposes), were introduced and tested on a real platform (laboratory environment and an uncontrolled environment - Moliceiros da Ria de Aveiro) to demonstrate that, in fact, the objective of LRBFAdvanced is fulfilled and achieved in practice. After analyzing the obtained results, it is concluded that the proposed new strategy, called LRBFAdvanced, fulfilled the main objective proposed, namely, the reduction of control and data overhead in the vehicular networkMestrado em Engenharia de Computadores e Telemátic

Information Fusion Methodology for Enhancing Situation Awareness in Connected Cars Environment

This dissertation introduces novel approaches to develop a comprehensive model to address situation awareness in the Internet of Cars, called Attention Assist Framework (AAF). The proposed framework utilizes both Low-Level Data Fusion (LLDF), and High-Level Information Fusion (HLIF) to implement traffic entity, situation, and impact assessment, as well as decision making. The Internet of Cars is the convergence of the Internet of Things and Vehicular Ad-hoc Networks (VANETs). In fact, VANETs are the communication platforms that make possible the implementation of the Internet of Cars, and has become an integral part of this research field due to its major role to improve vehicle and road safety, traffic efficiency, and convenience as well as comfort to both drivers and passengers. Significant amount of VANETs research work has been focused on specific areas such as safety, routing, broadcasting, Quality of Service (QoS), and security. Among them, road safety issues are deemed one of the most challenging problems of VANETs. Specifically, lack of proper situational awareness of drivers has been shown to be the main cause of road accidents which makes it a major factor in road safety. The traffic entity assessment relies on a LLDF framework that is able to incorporate various multi-sensor data fusion approaches with means of communication links in VANETs. This is used to implement a cooperative localization approach through fusing common data fusion methods, such as Extended Kalman Filter (EKF) and Unscented Transform (UT), and vehicle-to-vehicle communication in VANETs. Furthermore, traffic situation assessment is based on a fuzzy extension to the Multi-Entity Bayesian Networks (MEBNs), which exploit the expressiveness of first-order logic for semantic relations, and the strength of the Fuzzy Bayesian Networks in handling uncertainty, while tackling the inherent vagueness in the soft data created by human entities. Finally, the impact assessment and decision making is realized through incorporating notions of game theory into Fuzzy-MEBNs, and introducing Active Fuzzy-MEBN (ATFY-MEBN), which is capable in hypothesizing future situations by assessing the impact of the current situation upon taking the actions indicated by an optimal strategy. In fact, such strategies are achieved through solving the games that are generated through a novel situation-specific normal form games generation algorithm that aims to create games based on the given context. In general, ATFY-MEBN presents the concepts of players and actions, and includes new game components, along with a 2-tier architecture, to efficiently model impact assessment and decision making. To demonstrate the capabilities of the proposed framework, a collision warning system simulator is developed, which evaluates the likelihood of a vehicle being in a near-collision situation using a wide variety of both local and global information sources available in the VANETs environment, and suggests an optimal action by assessing the impact of the current situation through generating and solving situation-specific games. Accordingly, first, the entities that highly influence the safety aspect, as well as both their casual and semantic relationships are identified. Next, an ATFY-MEBN-based model is presented, which allows for modeling these entities along with their relationships in specific contexts, assessing the current states of the situations of interest, predicting their future states, and finally suggesting optimal decision. Therefore, if the likelihood of being in a near-collision situation is determined to be high, and if the relevant situation-specific game is generated, then the impact of deciding on different combinations of actions that the game players take are calculated through a pre-fixed payoff function. Finally, the completed game is solved by finding its dominant strategy, that subsequently, results in proposing the optimal action to the driver. Our experimental results are divided into three main sections, through which we evaluate the capabilities of the traffic entity, situation, and impact assessment methods. Accordingly, the performance of the proposed cooperative localization approach is assessed by comparing its results with the ground truth solution and that of the other localization methods in various driving test cases. Moreover, two distinct single-vehicle and multi-vehicles categories of driving scenarios, as well as a novel hybrid MEBN inference, demonstrate the capabilities of the proposed traffic assessment model to efficiently achieve situation and threat assessment on the road. Finally, the impact assessment and decision making models are evaluated through two different scenarios of driving in highway and intersection that are formed with various number of player vehicles, and their actions