Mean-Field-Type Games in Engineering

A mean-field-type game is a game in which the instantaneous payoffs and/or the state dynamics functions involve not only the state and the action profile but also the joint distributions of state-action pairs. This article presents some engineering applications of mean-field-type games including road traffic networks, multi-level building evacuation, millimeter wave wireless communications, distributed power networks, virus spread over networks, virtual machine resource management in cloud networks, synchronization of oscillators, energy-efficient buildings, online meeting and mobile crowdsensing.Comment: 84 pages, 24 figures, 183 references. to appear in AIMS 201

implications to CRM and public policy

Thesis(Doctoral) --KDI School:Ph.D in Public Policy,2017With the advent of the Internet and Mobile Communications, the nature of communication has changed significantly over the past few decades .The promotion of technologies among the common people has been found to be an important element of public policy to reduce the digital divide. The rapid advancement of information technology (IT), automation systems and data communications systems leads to improvement of intelligent transport systems (ITS). ITS covers all branches of transportation and involves all dynamically interacting elements of transportation system, i.e. transport means, infrastructure, drivers and commuters. However, few researches have been carried out in the context of public sectors, especially that involving ITS. The purpose of this study is to investigate the justice dimensions that influence satisfaction and public confidence in the context of ITS and to explore implications to Citizen/Customer Relationship Management (CRM) and public policy. This study investigates the following research questions: i) Do levels of perceived justice (distributive, procedural and interactional) in ITS environment affect levels of satisfaction/dissatisfaction? ii) Do levels of satisfaction form ITS affect levels of public confidence? iii) Do levels of dissatisfaction form ITS affect levels of willingness to complain? iv) Do levels of dissatisfaction form ITS affect levels of complaining behavior? v) Do levels of complaining behavior in ITS environment affect levels of satisfaction with complaint handling when the complaints are resolved based on three dimensions (distributive, procedural and interactional)of justice? vi) Do levels of willingness to complain in ITS environment affect levels of public confidence? vii) Do levels of satisfaction with complaint handling in ITS environment affect levels of public confidence? The findings of this study imply that ITS users are more importantly perceive to equity and equality issues, or distributive justice. The employment of ITS should not be limited to the technical aspects of ITS, but should focus more attention on the subjective domain of justice. The results of this study also have important implications for public complaint handling in terms of increasing public satisfaction with ITS, which is crucial for CRM.Part I: Exploring Satisfaction/Dissatisfaction and Public Confidence in the ITS Environment; Implications to CRM and Public Policy Part II: ComparingSatisfaction/Dissatisfaction and Public Confidence in the ITS Environment in Public and Private Transportation Part III: Implementation Strategy of ITS in Developing CountriesdoctoralpublishedA. K. M. Anisur RAHMAN

Service-Driven Networking

This thesis presents our research on service-driven networking, which is a general design framework for service quality assurance and integrated network and service management in large scale multi-domain networks. The philosophy is to facilitate bi-party open participation among the users and the providers of network services in order to bring about better service customization and quality assurance, without sacrificing the autonomy and objectives of the individual entities. Three primary research topics are documented: service composition and adaptation, self-stabilization in uncoordinated environment, and service quality modeling. The work involves theoretical analysis, algorithm design, and simulations as evaluation methodology

Nudging travellers to societally favourable routes: The impact of visual communication and emotional responses on decision making

As urbanisation increases, in many places, the transport system is suffering from problems that may affect large parts of the urban population, such as traffic congestion or increased air pollution. In both cases, a better distribution of traffic flows could contribute to establishing a more sustainable transport system, and to improve the situation from a societal point of view. In this paper, we use cartographic symbolisation for communicating favourability of route options for achieving a societal benefit. Since map symbols can evoke different emotional responses in the viewer, we investigate to which extent map symbols evoke positive and negative emotions and whether these influence route choice decision making. We created different cartographic visualisations and designed a user study that investigates the effectiveness and suitability of these different visualisation variants for influencing route choice based on two scenarios: traffic and air quality. Fourteen route maps were prepared using different map symbols to symbolise societally favourable and non-favourable route options. The results of this study show that map symbols can be used effectively for influencing route choice towards choosing the favourable route for the two tested scenarios. While visualisations that modify only lines were more effective in the traffic scenario, area symbol modifications were more effective for the air quality scenario. The symbolisation evoked a wide range of emotions in participants. While non-favourable routes mainly evoke negative emotions (particularly fear), favourable routes mainly evoked positive emotions (particularly contentment) or no emotions. The results further demonstrate that for some of the visualisation variants, emotions felt in response to the map visualisations contributed significantly to changing the route choice decisions in favour of the societally favourable route option. The findings of this research demonstrate the relationship between route choice behaviour and emotional responses elicited by map symbols

Towards causal federated learning : a federated approach to learning representations using causal invariance

Federated Learning is an emerging privacy-preserving distributed machine learning approach to building a shared model by performing distributed training locally on participating devices (clients) and aggregating the local models into a global one. As this approach prevents data collection and aggregation, it helps in reducing associated privacy risks to a great extent. However, the data samples across all participating clients are usually not independent and identically distributed (non-i.i.d.), and Out of Distribution (OOD) generalization for the learned models can be poor. Besides this challenge, federated learning also remains vulnerable to various attacks on security wherein a few malicious participating entities work towards inserting backdoors, degrading the generated aggregated model as well as inferring the data owned by participating entities. In this work, we propose an approach for learning invariant (causal) features common to all participating clients in a federated learning setup and analyse empirically how it enhances the Out of Distribution (OOD) accuracy as well as the privacy of the final learned model. Although Federated Learning allows for participants to contribute their local data without revealing it, it faces issues in data security and in accurately paying participants for quality data contributions. In this report, we also propose an EOS Blockchain design and workflow to establish data security, a novel validation error based metric upon which we qualify gradient uploads for payment, and implement a small example of our Blockchain Causal Federated Learning model to analyze its performance with respect to robustness, privacy and fairness in incentivization.L’apprentissage fédéré est une approche émergente d’apprentissage automatique distribué préservant la confidentialité pour créer un modèle partagé en effectuant une formation distribuée localement sur les appareils participants (clients) et en agrégeant les modèles locaux en un modèle global. Comme cette approche empêche la collecte et l’agrégation de données, elle contribue à réduire dans une large mesure les risques associés à la vie privée. Cependant, les échantillons de données de tous les clients participants sont généralement pas indépendante et distribuée de manière identique (non-i.i.d.), et la généralisation hors distribution (OOD) pour les modèles appris peut être médiocre. Outre ce défi, l’apprentissage fédéré reste également vulnérable à diverses attaques contre la sécurité dans lesquelles quelques entités participantes malveillantes s’efforcent d’insérer des portes dérobées, dégradant le modèle agrégé généré ainsi que d’inférer les données détenues par les entités participantes. Dans cet article, nous proposons une approche pour l’apprentissage des caractéristiques invariantes (causales) communes à tous les clients participants dans une configuration d’apprentissage fédérée et analysons empiriquement comment elle améliore la précision hors distribution (OOD) ainsi que la confidentialité du modèle appris final. Bien que l’apprentissage fédéré permette aux participants de contribuer leurs données locales sans les révéler, il se heurte à des problèmes de sécurité des données et de paiement précis des participants pour des contributions de données de qualité. Dans ce rapport, nous proposons également une conception et un flux de travail EOS Blockchain pour établir la sécurité des données, une nouvelle métrique basée sur les erreurs de validation sur laquelle nous qualifions les téléchargements de gradient pour le paiement, et implémentons un petit exemple de notre modèle d’apprentissage fédéré blockchain pour analyser ses performances

Connected Car: technologies, issues, future trends

The connected car -a vehicle capable of accessing to the Internet, of communicating with smart devices as well as other cars and road infrastructures, and of collecting real-time data from multiple sources- is likely to play a fundamental role in the foreseeable Internet Of Things. In a context ruled by very strong competitive forces, a significant amount of car manufacturers and software and hardware developers have already embraced the challenge of providing innovative solutions for new generation vehicles. Today’s cars are asked to relieve drivers from the most stressful operations needed for driving, providing them with interesting and updated entertainment functions. In the meantime, they have to comply to the increasingly stringent standards about safety and reliability. The aim of this paper is to provide an overview of the possibilities offered by connected functionalities on cars and the associated technological issues and problems, as well as to enumerate the currently available hardware and software solutions and their main features

Enabling Multipath and Multicast Data Transmission in Legacy and Future Internet

The quickly growing community of Internet users is requesting multiple applications and services. At the same time the structure of the network is changing. From the performance point of view, there is a tight interplay between the application and the network design. The network must be constructed to provide an adequate performance of the target application. In this thesis we consider how to improve the quality of users' experience concentrating on two popular and resource-consuming applications: bulk data transfer and real-time video streaming. We share our view on the techniques which enable feasibility and deployability of the network functionality leading to unquestionable performance improvement for the corresponding applications. Modern mobile devices, equipped with several network interfaces, as well as multihomed residential Internet hosts are capable of maintaining multiple simultaneous attachments to the network. We propose to enable simultaneous multipath data transmission in order to increase throughput and speed up such bandwidth-demanding applications as, for example, file download. We design an extension for Host Identity Protocol (mHIP), and propose a multipath data scheduling solution on a wedge layer between IP and transport, which effectively distributes packets from a TCP connection over available paths. We support our protocol with a congestion control scheme and prove its ability to compete in a friendly manner against the legacy network protocols. Moreover, applying game-theoretic analytical modelling we investigate how the multihomed HIP multipath-enabled hosts coexist in the shared network. The number of real-time applications grows quickly. Efficient and reliable transport of multimedia content is a critical issue of today's IP network design. In this thesis we solve scalability issues of the multicast dissemination trees controlled by the hybrid error correction. We propose a scalable multicast architecture for potentially large overlay networks. Our techniques address suboptimality of the adaptive hybrid error correction (AHEC) scheme in the multicast scenarios. A hierarchical multi-stage multicast tree topology is constructed in order to improve the performance of AHEC and guarantee QoS for the multicast clients. We choose an evolutionary networking approach that has the potential to lower the required resources for multimedia applications by utilizing the error-correction domain separation paradigm in combination with selective insertion of the supplementary data from parallel networks, when the corresponding content is available. Clearly both multipath data transmission and multicast content dissemination are the future Internet trends. We study multiple problems related to the deployment of these methods.Internetin nopeasti kasvava käyttäjäkunta vaatii verkolta yhä enemmän sovelluksia ja palveluita. Samaan aikaan verkon rakenne muuttuu. Suorituskyvyn näkökulmasta on olemassa selvä vuorovaikutussovellusten ja verkon suunnittelun välillä. Verkko on rakennettava siten, että se pystyy takaamaan riittävän suorituskyvyn halutuille palveluille. Tässä väitöskirjassa pohditaan, miten verkon käyttökokemusta voidaan parantaa keskittyen kahteen suosittuun ja resursseja vaativaan sovellukseen: tiedonsiirtoon ja reaaliaikaiseen videon suoratoistoon. Esitämme näkemyksemme tekniikoista, jotka mahdollistavat tarvittavien verkkotoiminnallisuuksien helpon toteuttavuuden sekä kiistatta parantavat sovelluksien suorityskykyä. Nykyaikaiset mobiililaitteet monine verkkoyhteyksineen, kuten myös kotitietokoneet, pystyvät ylläpitämään monta internet-yhteyttä samanaikaisesti. Siksi ehdotamme monikanavaisen tiedonsiirron käyttöä suorituskyvyn parantamiseksi ja etenkin vaativien verkkosovelluksien, kuten tiedostonsiirron, nopeuttamiseksi. Tässä väitöskirjassa suunnitellaan Host Identity Protocol (mHIP) -laajennus, sekä esitetään tiedonsiirron vuorotteluratkaisu, joka hajauttaa TCP-yhteyden tiedonsiirtopaketit käytettävissä oleville kanaville. Protokollamme tueksi luomme myös ruuhkautumishallinta-algoritmin ja näytämme sen pystyvän toimimaan yhteen nykyisien verkkoprotokollien kanssa. Tämän lisäksi tutkimme peliteoreettista mallinnusta käyttäen, miten monikanavaiset HIP-verkkopäätteet toimivat muiden kanssa jaetuissa verkoissa. Reaaliaikaisten sovellusten määrä kasvaa nopeasti. Tehokas ja luotettava multimediasisällön siirto on olennainen vaatimus nykypäivän IP-verkoissa. Tässä työssä ratkaistaan monilähetyksen (multicast) jakelustruktuurin skaalautuvuuteen liittyviä ongelmia. Ehdotamme skaalautuvaa monilähetysarkkitehtuuria suurille peiteverkoille. Ratkaisumme puuttuu adaptiivisen virhekorjauksen (Adaptive Hybrid Error Correction, AHEC) alioptimaalisuuteen monilähetystilanteissa. Luomme hierarkisen monivaiheisen monilähetyspuutopologian parantaaksemme AHECin suorituskykyä, sekä taataksemme monilähetysasiakkaiden palvelun laadun. Valitsimme evoluutiomaisen lähestymistavan, jolla on potentiaalia keventää multimediasovelluksien verkkoresurssivaatimuksia erottamalla virhekorjauksen omaksi verkkotunnuksekseen, sekä käyttämällä valikoivaa täydentävää tiedonlisäystä rinnakkaisverkoista vastaavan sisällön ollessa saatavilla. Sekä monikanava- että monilähetystiedonsiirto ovat selvästi osa internetin kehityssuuntaa. Tässä väitöskirjassa tutkimme monia ongelmia näiden tekniikoiden käyttöönottoon liittyen