Context aware advertising

IP Television (IPTV) has created a new arena for digital advertising that has not been explored to its full potential yet. IPTV allows users to retrieve on demand content and recommended content; however, very limited research has been applied in the domain of advertising in IPTV systems. The diversity of the field led to a lot of mature efforts in the fields of content recommendation and mobile advertising. The introduction of IPTV and smart devices led to the ability to gather more context information that was not subject of study before. This research attempts at studying the different contextual parameters, how to enrich the advertising context to tailor better ads for users, devising a recommendation engine that utilizes the new context, building a prototype to prove the viability of the system and evaluating it on different quality of service and quality of experience measures. To tackle this problem, a review of the state of the art in the field of context-aware advertising as well as the related field of context-aware multimedia have been studied. The intent was to come up with the most relevant contextual parameters that can possibly yield a higher percentage precision for recommending advertisements to users. Subsequently, a prototype application was also developed to validate the feasibility and viability of the approach. The prototype gathers contextual information related to the number of viewers, their age, genders, viewing angles as well as their emotions. The gathered context is then dispatched to a web service which generates advertisement recommendations and sends them back to the user. A scheduler was also implemented to identify the most suitable time to push advertisements to users based on their attention span. To achieve our contributions, a corpus of 421 ads was gathered and processed for streaming. The advertisements were displayed in reality during the holy month of Ramadan, 2016. A data gathering application was developed where sample users were presented with 10 random ads and asked to rate and evaluate the advertisements according to a predetermined criteria. The gathered data was used for training the recommendation engine and computing the latent context-item preferences. This also served to identify the performance of a system that randomly sends advertisements to users. The resulting performance is used as a benchmark to compare our results against. When it comes to the recommendation engine itself, several implementation options were considered that pertain to the methodology to create a vector representation of an advertisement as well as the metric to use to measure the similarity between two advertisement vectors. The goal is to find a representation of advertisements that circumvents the cold start problem and the best similarity measure to use with the different vectorization techniques. A set of experiments have been designed and executed to identify the right vectorization methodology and similarity measure to apply in this problem domain. To evaluate the overall performance of the system, several experiments were designed and executed that cover different quality aspects of the system such as quality of service, quality of experience and quality of context. All three aspects have been measured and our results show that our recommendation engine exhibits a significant improvement over other mechanisms of pushing ads to users that are employed in currently existing systems. The other mechanisms placed in comparison are the random ad generation and targeted ad generation. Targeted ads mechanism relies on demographic information of the viewer with disregard to his/her historical consumption. Our system showed a precision percentage of 69.70% which means that roughly 7 out of 10 recommended ads are actually liked and viewed to the end by the viewer. The practice of randomly generating ads yields a result of 41.11% precision which means that only 4 out of 10 recommended ads are actually liked by viewers. The targeted ads system resulted in 51.39% precision. Our results show that a significant improvement can be introduced when employing context within a recommendation engine. When introducing emotion context, our results show a significant improvement in case the user’s emotion is happiness; however, it showed a degradation of performance when the user’s emotion is sadness. When considering all emotions, the overall results did not show a significant improvement. It is worth noting though that ads recommended based on detected emotions using our systems proved to always be relevant to the user\u27s current mood

Survey of Transportation of Adaptive Multimedia Streaming service in Internet

[DE] World Wide Web is the greatest boon towards the technological advancement of modern era. Using the benefits of Internet globally, anywhere and anytime, users can avail the benefits of accessing live and on demand video services. The streaming media systems such as YouTube, Netflix, and Apple Music are reining the multimedia world with frequent popularity among users. A key concern of quality perceived for video streaming applications over Internet is the Quality of Experience (QoE) that users go through. Due to changing network conditions, bit rate and initial delay and the multimedia file freezes or provide poor video quality to the end users, researchers across industry and academia are explored HTTP Adaptive Streaming (HAS), which split the video content into multiple segments and offer the clients at varying qualities. The video player at the client side plays a vital role in buffer management and choosing the appropriate bit rate for each such segment of video to be transmitted. A higher bit rate transmitted video pauses in between whereas, a lower bit rate video lacks in quality, requiring a tradeoff between them. The need of the hour was to adaptively varying the bit rate and video quality to match the transmission media conditions. Further, The main aim of this paper is to give an overview on the state of the art HAS techniques across multimedia and networking domains. A detailed survey was conducted to analyze challenges and solutions in adaptive streaming algorithms, QoE, network protocols, buffering and etc. It also focuses on various challenges on QoE influence factors in a fluctuating network condition, which are often ignored in present HAS methodologies. Furthermore, this survey will enable network and multimedia researchers a fair amount of understanding about the latest happenings of adaptive streaming and the necessary improvements that can be incorporated in future developments.Abdullah, MTA.; Lloret, J.; Canovas Solbes, A.; García-García, L. (2017). Survey of Transportation of Adaptive Multimedia Streaming service in Internet. Network Protocols and Algorithms. 9(1-2):85-125. doi:10.5296/npa.v9i1-2.12412S8512591-

STUDY OF QUALITY OF SERVICE IN 4G AND 5G NETWORKS

[ES] El estudio de la calidad de servicio (QoS) es cada vez más importante, ya que la QoS se considera tan importante como la seguridad de la red. Es vital ofrecer suficiente QoS en servicios considerados críticos como las redes de comunicaciones en emergencias, el control remoto de maquinaria, o en el futuro, poder realizar operaciones a distancia gracias a tecnología como el 5G. Esta tesis presenta el estudio de la calidad de servicio en las redes de comunicaciones móviles. Los objetivos principales fueron describir los aspectos teóricos más relevantes en las redes 4G y 5G, los cambios en el campo de los nuevos desarrollos, G-NetTrack Pro y Qosium, las dos herramientas para realizar mediciones de QoS en redes móviles y, finalmente, realizar mediciones de QoS en un entorno de investigación. Se espera que de los resultados obtenidos se extraigan conclusiones sobre las herramientas utilizadas para futuros proyectos de investigación en materia de comunicaciones móviles. La metodología consistió en medir el rendimiento de una red 4G mediante la medición de la calidad de servicio suministrada en dos servicios con requisitos muy diferentes. Medición de la calidad de servicio en llamadas de voz sobre protocolo de Internet [VoIP] y medición de la calidad de servicio en una transmisión de vídeo. Con los resultados obtenidos se ha podido observar el excelente rendimiento de la red en diversas condiciones de interior y exterior, y se han podido aplicar los conocimientos teóricos previamente estudiados. Por último, se han identificado las ventajas y desventajas de las herramientas utilizadas. Se espera que esta tesis sea útil para futuros proyectos del grupo de investigación 5GTNT que midan la QoS con las herramientas descritas. Además, los resultados y conclusiones también pueden ser utilizados por terceros, ya que los resultados y conclusiones pueden ser útiles para entornos de investigación e industriales.[EN] The study of Quality of Service (QoS) is becoming increasingly important since QoS is considered equally important as network security. It is vital to offer sufficient QoS in services considered critical such as communications networks in emergencies, remote control of machinery, or in the future, to be able to perform remote operations thanks to technology such as 5G. This thesis presents the study of QoS in mobile communication networks. The main objectives were to describe the most relevant theoretical aspects in 4G and 5G networks, the changes in the field of new developments, G-NetTrack Pro and Qosium, the two tools to perform QoS measurements in mobile networks and finally, to perform QoS measurements in a research environment. It was expected that from the results obtained; conclusions will be drawn about the tools used for future research projects in mobile communications. The methodology consisted of measuring the performance of a 4G network by measuring the QoS delivered in two services with very different requirements. Measuring QoS in Voice Over Internet Protocol [VoIP] calls and measuring QoS in a video-streaming. With the results obtained, it has been possible to observe the excellent performance of the network under various indoor and outdoor conditions, and it has been possible to apply the theoretical knowledge previously studied. Finally, the advantages and disadvantages of the tools used have been identified. It is expected that this thesis will be useful for future projects of the research group 5GTNT measuring QoS with the described tools. In addition, the results and conclusions can also be used by third parties since the results and conclusions can be useful for research and industry environments.Pérez-Chuecos Alcaraz, PA. (2020). STUDY OF QUALITY OF SERVICE IN 4G AND 5G NETWORKS. http://hdl.handle.net/10251/152361TFG

Quadri-dimensional approach for data analytics in mobile networks

The telecommunication market is growing at a very fast pace with the evolution of new technologies to support high speed throughput and the availability of a wide range of services and applications in the mobile networks. This has led to a need for communication service providers (CSPs) to shift their focus from network elements monitoring towards services monitoring and subscribers’ satisfaction by introducing the service quality management (SQM) and the customer experience management (CEM) that require fast responses to reduce the time to find and solve network problems, to ensure efficiency and proactive maintenance, to improve the quality of service (QoS) and the quality of experience (QoE) of the subscribers. While both the SQM and the CEM demand multiple information from different interfaces, managing multiple data sources adds an extra layer of complexity with the collection of data. While several studies and researches have been conducted for data analytics in mobile networks, most of them did not consider analytics based on the four dimensions involved in the mobile networks environment which are the subscriber, the handset, the service and the network element with multiple interface correlation. The main objective of this research was to develop mobile network analytics models applied to the 3G packet-switched domain by analysing data from the radio network with the Iub interface and the core network with the Gn interface to provide a fast root cause analysis (RCA) approach considering the four dimensions involved in the mobile networks. This was achieved by using the latest computer engineering advancements which are Big Data platforms and data mining techniques through machine learning algorithms.Electrical and Mining EngineeringM. Tech. (Electrical Engineering

Network sharing through service outsourcing in inter-domain IMS frameworks

Includes abstract.Includes bibliographical references (leaves 161-167).Resource sharing can be used as a short-term solution to the imbalance between the supply and demand of network resources. Resources sharing enables operators to provide services to their subscribers using networks belonging to other operators. Resource sharing in mobile networks is increasingly becoming an option for operators to provide service to their subscribers. In this thesis we explore a mechanism for sharing access network resources that utilises negotiable short-term Service Level Agreements (SLA) that can easily adapt to changing network conditions. Through this mechanism operators of resource constrained networks may use near real time dynamic SLAs to negotiate network access services for their subscribers. We refer to this form of resource sharing as 'Service Outsourcing'

A reduced reference video quality assessment method for provision as a service over SDN/NFV-enabled networks

139 p.The proliferation of multimedia applications and services has generarted a noteworthy upsurge in network traffic regarding video content and has created the need for trustworthy service quality assessment methods. Currently, predominent position among the technological trends in telecommunication networkds are Network Function Virtualization (NFV), Software Defined Networking (SDN) and 5G mobile networks equipped with small cells. Additionally Video Quality Assessment (VQA) methods are a very useful tool for both content providers and network operators, to understand of how users perceive quality and this study the feasibility of potential services and adapt the network available resources to satisfy the user requirements

A reduced reference video quality assessment method for provision as a service over SDN/NFV-enabled networks

139 p.The proliferation of multimedia applications and services has generarted a noteworthy upsurge in network traffic regarding video content and has created the need for trustworthy service quality assessment methods. Currently, predominent position among the technological trends in telecommunication networkds are Network Function Virtualization (NFV), Software Defined Networking (SDN) and 5G mobile networks equipped with small cells. Additionally Video Quality Assessment (VQA) methods are a very useful tool for both content providers and network operators, to understand of how users perceive quality and this study the feasibility of potential services and adapt the network available resources to satisfy the user requirements

Novel applications of Machine Learning to Network Traffic Analysis and Prediction

It is now clear that machine learning will be widely used in future telecommunication networks as it is increasingly used in today's networks. However, despite its increasing application and its enormous potential, there are still many areas in which the new techniques developed in the area of machine learning are not yet fully utilized. The aim of this thesis is to present the application of innovative techniques of machine learning (ML-Machine Learning) in the field of Telecommunications, and specifically to problems related to the analysis and prediction of traffic in data networks (NTAP - Network Traffic Analysis and Prediction). The applications of NTAP are very broad, so this thesis focuses on the following five specific areas: - Prediction of connectivity of wireless devices. - Security intrusion detection, using network traffic information - Classification of network traffic, using the headers of the transmitted network packets - Estimation of the quality of the experience perceived by the user (QoE) when viewing multimedia streaming, using aggregate information of the network packets - Generation of synthetic traffic associated with security attacks and use of that synthetic traffic to improve security intrusion detection algorithms. The final intention is to create prediction and analysis models that produce improvements in the NTAP areas mentioned above. With this objective, this thesis provides advances in the application of machine learning techniques to the area of NTAP. These advances consist of: - Development of new machine learning models and architectures for NTAP - Define new ways to structure and transform training data so that existing machine learning models can be applied to specific NTAP problems. - Define algorithms for the creation of synthetic network traffic associated with specific events in the operation of the network (for example, specific types of intrusions), ensuring that the new synthetic data can be used as new training data. - Extension and application of classic models of machine learning to the area of NTAP, obtaining improvements in the classification or regression metrics and/or improvements in the performance measures of the algorithms (e.g. training time, prediction time, memory needs, ...).Departamento de Teoría de la Señal y Comunicaciones e Ingeniería TelemáticaDoctorado en Tecnologías de la Información y las Telecomunicacione

Enhanced Quality of Experience Based on Enriched Network Centric and Access Control Mechanisms

In the digital world service provisioning in user satisfying quality has become the goal of any content or network provider. Besides having satisfied and therefore, loyal users, the creation of sustainable revenue streams is the most important issue for network operators [1], [2], [3]. The motivation of this work is to enhance the quality of experience of users when they connect to the Internet, request application services as well as to maintain full service when these users are on the move in WLAN based access networks. In this context, the aspect of additional revenue creation for network operators is considered as well. The enhancements presented in this work are based on enriched network centric and access control mechanisms which will be achieved in three different areas of networks capabilities, namely the network performance, the network access and the network features themselves. In the area of network performance a novel authentication and authorisation method is introduced which overcomes the drawback of long authentication time in the handover procedure as required by the generic IEEE 802.1X process using the EAP-TLS method. The novel sequential authentication solution reduces the communication interruption time in a WLAN handover process of currently several hundred milliseconds to some milliseconds by combining the WPA2 PSK and the WPA2 EAP-TLS. In the area of usability a new user-friendly hotspot registration and login mechanisms is presented which significantly simplifies how users obtain WLAN hotspot login credentials and logon to a hotspot. This novel barcode initiated hotspot auto-login solution obtains user credentials through a simple SMS and performs an auto-login process that avoids the need to enter user name and password on the login page manually. In the area of network features a new system is proposed which overcomes the drawback that users are not aware of the quality in which a service can be provided prior to starting the service. This novel graceful denial of service solution informs the user about the expected application service quality before the application service is started