93 research outputs found

    Building the Future Internet through FIRE

    Get PDF
    The Internet as we know it today is the result of a continuous activity for improving network communications, end user services, computational processes and also information technology infrastructures. The Internet has become a critical infrastructure for the human-being by offering complex networking services and end-user applications that all together have transformed all aspects, mainly economical, of our lives. Recently, with the advent of new paradigms and the progress in wireless technology, sensor networks and information systems and also the inexorable shift towards everything connected paradigm, first as known as the Internet of Things and lately envisioning into the Internet of Everything, a data-driven society has been created. In a data-driven society, productivity, knowledge, and experience are dependent on increasingly open, dynamic, interdependent and complex Internet services. The challenge for the Internet of the Future design is to build robust enabling technologies, implement and deploy adaptive systems, to create business opportunities considering increasing uncertainties and emergent systemic behaviors where humans and machines seamlessly cooperate

    Web service composition: A survey of techniques and tools

    Get PDF
    Web services are a consolidated reality of the modern Web with tremendous, increasing impact on everyday computing tasks. They turned the Web into the largest, most accepted, and most vivid distributed computing platform ever. Yet, the use and integration of Web services into composite services or applications, which is a highly sensible and conceptually non-trivial task, is still not unleashing its full magnitude of power. A consolidated analysis framework that advances the fundamental understanding of Web service composition building blocks in terms of concepts, models, languages, productivity support techniques, and tools is required. This framework is necessary to enable effective exploration, understanding, assessing, comparing, and selecting service composition models, languages, techniques, platforms, and tools. This article establishes such a framework and reviews the state of the art in service composition from an unprecedented, holistic perspective

    Building the Future Internet through FIRE

    Get PDF
    The Internet as we know it today is the result of a continuous activity for improving network communications, end user services, computational processes and also information technology infrastructures. The Internet has become a critical infrastructure for the human-being by offering complex networking services and end-user applications that all together have transformed all aspects, mainly economical, of our lives. Recently, with the advent of new paradigms and the progress in wireless technology, sensor networks and information systems and also the inexorable shift towards everything connected paradigm, first as known as the Internet of Things and lately envisioning into the Internet of Everything, a data-driven society has been created. In a data-driven society, productivity, knowledge, and experience are dependent on increasingly open, dynamic, interdependent and complex Internet services. The challenge for the Internet of the Future design is to build robust enabling technologies, implement and deploy adaptive systems, to create business opportunities considering increasing uncertainties and emergent systemic behaviors where humans and machines seamlessly cooperate

    Addressing training data sparsity and interpretability challenges in AI based cellular networks

    Get PDF
    To meet the diverse and stringent communication requirements for emerging networks use cases, zero-touch arti cial intelligence (AI) based deep automation in cellular networks is envisioned. However, the full potential of AI in cellular networks remains hindered by two key challenges: (i) training data is not as freely available in cellular networks as in other fields where AI has made a profound impact and (ii) current AI models tend to have black box behavior making operators reluctant to entrust the operation of multibillion mission critical networks to a black box AI engine, which allow little insights and discovery of relationships between the configuration and optimization parameters and key performance indicators. This dissertation systematically addresses and proposes solutions to these two key problems faced by emerging networks. A framework towards addressing the training data sparsity challenge in cellular networks is developed, that can assist network operators and researchers in choosing the optimal data enrichment technique for different network scenarios, based on the available information. The framework encompasses classical interpolation techniques, like inverse distance weighted and kriging to more advanced ML-based methods, like transfer learning and generative adversarial networks, several new techniques, such as matrix completion theory and leveraging different types of network geometries, and simulators and testbeds, among others. The proposed framework will lead to more accurate ML models, that rely on sufficient amount of representative training data. Moreover, solutions are proposed to address the data sparsity challenge specifically in Minimization of drive test (MDT) based automation approaches. MDT allows coverage to be estimated at the base station by exploiting measurement reports gathered by the user equipment without the need for drive tests. Thus, MDT is a key enabling feature for data and artificial intelligence driven autonomous operation and optimization in current and emerging cellular networks. However, to date, the utility of MDT feature remains thwarted by issues such as sparsity of user reports and user positioning inaccuracy. For the first time, this dissertation reveals the existence of an optimal bin width for coverage estimation in the presence of inaccurate user positioning, scarcity of user reports and quantization error. The presented framework can enable network operators to configure the bin size for given positioning accuracy and user density that results in the most accurate MDT based coverage estimation. The lack of interpretability in AI-enabled networks is addressed by proposing a first of its kind novel neural network architecture leveraging analytical modeling, domain knowledge, big data and machine learning to turn black box machine learning models into more interpretable models. The proposed approach combines analytical modeling and domain knowledge to custom design machine learning models with the aim of moving towards interpretable machine learning models, that not only require a lesser training time, but can also deal with issues such as sparsity of training data and determination of model hyperparameters. The approach is tested using both simulated data and real data and results show that the proposed approach outperforms existing mathematical models, while also remaining interpretable when compared with black-box ML models. Thus, the proposed approach can be used to derive better mathematical models of complex systems. The findings from this dissertation can help solve the challenges in emerging AI-based cellular networks and thus aid in their design, operation and optimization

    Quality of experience characterization and provisioning in mobile cellular networks

    Get PDF
    Παραδοσιακά, οι προηγούμενες γενεές κινητών κυψελωτών δικτύων έχουν σχεδιαστεί με κριτήρια Ποιότητας Υπηρεσίας, έτσι ώστε να πληρούν συγκεκριμένες απαιτήσεις διαφόρων υπηρεσιών. Η «Ποιότητα Εμπειρίας» έχει, ωστόσο, πρόσφατα εμφανιστεί ως έννοια, επηρεάζοντας το σχεδιασμό των μελλοντικών γενεών των δικτύων, δίνοντας σαφή έμφαση στην πραγματικά επιτευχθείσα εμπειρία του τελικού χρήστη. Η εμφάνιση της έννοιας της Ποιότητας Εμπειρίας οφείλεται στην αναπόφευκτη, ισχυρή μετάβαση που βιώνει η βιομηχανία των Τηλεπικοινωνιών από συστημο-κεντρικά δίκτυα σε πιο χρηστο-κεντρικές λύσεις και στόχους. Οι πάροχοι κινητών δικτύων, οι πάροχοι υπηρεσιών, οι προγραμματιστές εφαρμογών, αλλά και άλλα ενδιαφερόμενα μέλη που εμπλέκονται στην αλυσίδα παροχής υπηρεσιών προσελκύονται από τις ευκαιρίες που μπορεί να προσφέρει η ενσωμάτωση γνώσης Ποιότητας Εμπειρίας στο επιχειρηματικό τους μοντέλο. Πράγματι, η παρεχόμενη Ποιότητα Εμπειρίας αποτελεί έναν καθοριστικό παράγοντα διαφοροποίησης μεταξύ των διαφόρων παικτών, μία τάση που αναμένεται να γίνει ακόμη πιο έντονη τα επόμενα χρόνια. Υποκινούμενη από αυτή την χρηστο-κεντρική τάση, η έρευνα που διεξάγεται σε αυτή τη διατριβή έχει ως στόχο την διερεύνηση των προκλήσεων και των ευκαιριών που προκύπτουν στα σύγχρονα κινητά κυψελωτά δίκτυα όταν λαμβάνεται υπόψιν η έννοια της Ποιότητας Εμπειρίας. Τέτοιες ευκαιρίες αφορούν, καταρχήν, τη δυνατότητα κατανόησης της Ποιότητας Εμπειρίας που επιτυγχάνει ένας πάροχος κατά την προσφορά μίας υπηρεσίας. Αυτό μπορεί να επιτευχθεί με την υλοποίηση και ενσωμάτωση μεθόδων αξιολόγησης Ποιότητας Εμπειρίας στην πραγματικού-χρόνου λειτουργία ενός δικτύου. Εν συνεχεία, ακολουθεί η εκμετάλλευση της συλλεγμένης ευφυΐας που σχετίζεται με την Ποιότητα Εμπειρίας, προκειμένου να επανεξεταστούν υφιστάμενοι μηχανισμοί επιπέδου δικτύου (π.χ., χρονο-προγραμματισμός ραδιοπόρων) ή μηχανισμοί επιπέδου εφαρμογής (π.χ., ροή βίντεο), αλλά και να προταθούν καινοτόμες διαστρωματικές προσεγγίσεις προς όφελος της Ποιότητας Εμπειρίας. Επιπλέον, υπάρχει η δυνατότητα πρότασης νέων αλγορίθμων που προκύπτουν από τα εγγενή χαρακτηριστικά της Ποιότητας Εμπειρίας, όπως η μη γραμμική επίδραση μετρικών Ποιότητας Υπηρεσίας στην Ποιότητα Εμπειρίας, με στόχο την περαιτέρω βελτίωσή της. Σε αυτή την κατεύθυνση, στην παρούσα διατριβή, διερευνώνται και αξιοποιούνται μοντέλα και μετρικές εκτίμησης Ποιότητας Εμπειρίας με στόχο την ποσοτικοποίησή της, έχοντας ως απώτερο στόχο την εισαγωγή βελτιώσεων στους υφιστάμενους μηχανισμούς κινητών κυψελωτών δικτύων. Ο πυρήνας αυτής της διατριβής είναι η πρόταση μίας κυκλικής διεργασίας παροχής Ποιότητας Εμπειρίας που επιτρέπει τον έλεγχο, την παρακολούθηση (ήτοι, τη μοντελοποίηση) και τη διαχείριση της Ποιότητας Εμπειρίας σε ένα κυψελωτό δίκτυο. Κάθε μία από αυτές τις λειτουργίες αναλύεται περαιτέρω, ενώ έμφαση δίνεται στις λειτουργίες μοντελοποίησης και διαχείρισης. Όσον αφορά τη μοντελοποίηση, γίνεται περιγραφή και ταξινόμηση των μεθόδων εκτίμησης και των δεικτών επιδόσεων Ποιότητας Εμπειρίας. Η παραμετρική εκτίμηση της ποιότητας αναδεικνύεται ως η πιο ελκυστική κατηγορία μοντελοποίησης Ποιότητας Εμπειρίας σε κινητά κυψελωτά δίκτυα, οπότε και περιγράφεται διεξοδικά για ευρέως χρησιμοποιούμενους τύπους υπηρεσιών, όπως η συνομιλία (φωνή) μέσω Internet Protocol (IP) και η μετάδοση βίντεο. Όσον αφορά τη διαχείριση Ποιότητας Εμπειρίας, προτείνονται νέοι μηχανισμοί που επιδεικνύουν βελτιώσεις στην εμπειρία των τελικών χρηστών, και συγκεκριμένα: α) ένα σχήμα ελέγχου των επικοινωνιών συσκευής-προς-συσκευή που λαμβάνει υπόψιν την εμπειρία των χρηστών, β) ένας «συνεπής» αλγόριθμος χρονο-προγραμματισμού ραδιοπόρων που βελτιώνει την Ποιότητα Εμπειρίας του χρήστη μετριάζοντας τις διακυμάνσεις της ρυθμαπόδοσης του δικτύου, και γ) ένας μηχανισμός προσαρμοστικής ροής βίντεο με γνώσεις «πλαισίου», ο οποίος επιτυγχάνει την εξάλειψη διακοπών του βίντεο σε συνθήκες χαμηλού εύρους ζώνης. Επιπλέον, προτείνεται μία εφαρμογή Ποιότητας Εμπειρίας βασισμένη στην αρχιτεκτονική Software-Defined Networking (SDN), ονόματι “QoE-SDN APP”, η οποία επιτρέπει την ανάδραση πληροφοριών δικτύου από παρόχους κινητής τηλεφωνίας σε παρόχους υπηρεσιών βίντεο, αναδεικνύοντας πλεονεκτήματα ως προς την Ποιότητα Εμπειρίας για τους πελάτες των παρόχων βίντεο αλλά και ως προς την εξοικονόμηση εύρους ζώνης για τους φορείς εκμετάλλευσης δικτύου. Εν κατακλείδι, η παρούσα διατριβή προωθεί την ενοποίηση του ερευνητικού πεδίου της Ποιότητας Εμπειρίας με τον τομέα των κινητών επικοινωνιών, καθώς και τη συνεργασία αμοιβαίου ενδιαφέροντος μεταξύ των παρόχων δικτύου (επίπεδο δικτύου) με τους παρόχους υπηρεσιών (επίπεδο εφαρμογής), αναδεικνύοντας την δυναμική από τέτοιου είδους προσεγγίσεις για όλους τους εμπλεκόμενους φορείς.Traditionally, previous generations of mobile cellular networks have been designed with Quality of Service (QoS) criteria in mind, so that they manage to meet specific service requirements. Quality of Experience (QoE) has, however, recently emerged as a concept, disrupting the design of future network generations by giving clear emphasis on the actually achieved user experience. The emergence of the QoE concept has been a result of the inevitable strong transition that the Telecom industry is currently experiencing from system-centric networks to more user-centric solutions and objectives. Mobile network operators, service providers, application developers, as well as other stakeholders involved in the service provisioning chain have been attracted by the opportunities that the integration of the QoE concept could bring to their business; indeed, the provisioned QoE constitutes a determining factor of differentiation among different stakeholders, a tendency which is expected to become even more intense in the years to come. Motivated by this boost towards user-centricity, the objective of the research conducted in this thesis is to explore the challenges and opportunities that arise in modern mobile cellular networks when QoE is considered. Such opportunities concern, first of all, the possibility to comprehend the QoE that a provider achieves when provisioning a service. This can be enabled by the implementation and integration of QoE assessment methods into the real-time operation of a network. Then, the next step is the exploitation of collected QoE-related intelligence in order to re-examine existing network-layer mechanisms (e.g., radio scheduling), or application-layer mechanisms (e.g., video streaming), as well as propose novel cross-layer approaches towards ameliorating the achieved QoE. Moreover, the opportunity emerges to propose novel algorithms that stem from the inherent idiosyncrasies of QoE, such as the non-linear impact of QoS-related parameters on QoE, as a way to further enhance the users’ QoE. In this direction, throughout this thesis, QoE estimation models and metrics are explored and exploited in order to quantify QoE and thus, to improve existing mechanisms of mobile cellular networks. The core of this thesis is the proposal of a QoE provisioning cycle that allows the control, monitoring (i.e., modeling) and management of QoE in a cellular network. Each one of these functions is further analyzed, while emphasis is given on the modeling and management operations. In terms of modeling, QoE assessment methods and QoE-related performance indicators are described and classified. Parametric quality estimation is identified as the most appealing type of QoE estimation in mobile cellular networks, thus, it is thoroughly described for widely used types of services, such as Voice over IP (VoIP) and video streaming. In terms of QoE management, novel QoE-aware mechanisms that demonstrate QoE improvements for the users are proposed, namely: a) a QoE-driven Device-to-Device (D2D) communication management scheme that enhances end-user QoE, b) a “consistent” radio scheduling algorithm that improves the end-user QoE by mitigating throughput fluctuations, and c) a context-aware HTTP Adaptive Streaming (HAS) mechanism that successfully mitigates stallings (i.e., video freezing events) in the context of bandwidth-challenging scenarios. Moreover, a programmable QoE-SDN APP into the Software-Defined Networking (SDN) architecture is introduced, which enables network feedback exposure from mobile network operators to video service providers, revealing QoE benefits for the customers of video providers and bandwidth savings for the network operators. Overall, this thesis promotes the uniting of the domain of QoE with the domain of mobile communications, as well as the collaboration of mutual-interest between mobile network operators (network layer) and service providers (application layer), presenting the high potential from such approaches for all involved stakeholders

    The e-Government Development Discourse

    Get PDF
    research agenda for e-Government. When e-Government was first conceived, it was designed upon basic technologies where the emphasis was only on the simple display of government information for citizens to read. Nowadays, e-Government design comprises many complicated modules such as upload and download consoles, two-way interaction consoles between citizens and government agents, integrated government business processes presenting the whole of government, and it does not depend solely on technology. The complexity of e-Government has now evolved to include political, cultural, economic, social and technical dimensions. Bringing all these difficult aspects together is so complicated that it needs carefully planned strategies informed by local contextual characteristics. Rather than giving formulaic definitions and conceptual standpoints on many aspects of e-Government, as is the case in many e-Government publications, this book will explore the frontiers of global knowledge value chains by discussing current and future dimensions of e-Government. For example, the book discusses the concept of data governance by exploring how actual opening up of government data can be achieved, especially in a developing world context. Further, the book posits that opening government data should be followed by the opening up of government business processes in order to peddle the concept of accountability and responsiveness. Much text on data governance has concentrated on articulating the basic definitions surrounding this concept. Another very important topic explored in this book is regarding how the concept of decolonisation can be extended to e-Government by providing practical examples as to how researchers in the developing world can contribute to the advancement of e-Government as a scientific field of enquiry and guide its implementation, thereof. Decolonisation is advocated for in e-Government research so that there is a balance in the inclusion of the Afrocentric knowledge into e-Government advancement other than over-reliance on the Euro-, Asia- and America-centric knowledge value chains (Mbembe 2015). As e-Government is a very expensive undertaking, the issue of funding has excluded African countries and a majority of the developing world from implementing e-Government. Despite funding being a critical cornerstone of e-Government development, there is a dearth of information on this topic. Therefore, this book provides a chapter which discusses traditional and innovative ways of funding e-Government design and implementation which can go a long way in improving e-Government penetration into the developing world. Further, the book explores how intelligent e-Government applications can be designed, especially in resource-constrained countries. A couple of emerging technology innovations such as fog computing and intelligent information technology are explored within the realm of e-Government design
    corecore