The ability for base stations to be able to beam-form their signals, directing the signal energy to specific users, is a topic of research that has been heavily studied during the last decades. The beam-forming technique aims to increase the signal-to-interference-and-noise-ratio of the user and, consequently, increase the capacity and coverage of the communication system. One such method is the Differential Beam-Forming technique, that has been developed at Ericsson Research. In this version of beam-forming, the beams can be dynamically sharpened and widened when tracking a specific terminal, to try to optimize the signal energy sent to that terminal. Beam-forming, however, makes the link-adaptation algorithm process substantially harder to perform. The reason for this is that the link-adaptation algorithm now has to take into account not only the changing radio environment, but also the changing transmit signal that is being beam-formed. Fortunately, since the beam-formed signal is known at the point of transmission, there should be a potential to utilize this knowledge to make the link-adaptation more efficient. This thesis, investigates how the link-adaptation algorithm could be changed to perform better in beam-forming setups, as well as what information from the beam-forming algorithm that could be included and utilized in the link-adaptation algorithm. This is done by designing and investigating three new link-adaptation algorithms, in the context of Differential Beam-Forming in an LTE FDD system. The algorithms that has been designed are both of a beam-forming-aware and beam-forming-unaware character, meaning if the beam-forming information is utilized within the algorithm, or not. These algorithms have been simulated for different base station antenna array-sizes. Unfortunately, due to simulator restrictions, the terminals have been simulated in a stationary environment, which has proven to be a limiting factor for the results. However, the results still show that smarter beam-forming-aware link-adaptation could possibly be used to increase the performance of the link-adaptation when using beam-forming.

published_or_final_version / Computer Science / Doctoral / Doctor of Philosophy

The transmitting of video content over Vehicular Ad Hoc Networks (VANETs) faces a great number of challenges caused by strict QoS (Quality of Service) requirements and highly dynamic network topology. In order to tackle these challenges, multipath forwarding schemes can be regarded as potential solutions. However, route coupling effect and the path length growth severely impair the performance of multipath schemes. In this thesis, the current research status about video streaming over VANETs as well as multipath transmissions are reviewed. With the demand to discover a more suitable solution, we propose the Location-Aware Multipath Video Streaming (LIAITHON+) protocol to address video streaming over urban VANETs. LIAITHON+ uses location information to discover relatively short paths with minimal route coupling effect. The performance results have shown it outperforms the underlying single path solution as well as the node-disjoint multipath solution. In addition, the impact of added redundancy on the multipath solution is investigated through LIAITHON+. According to the results, added redundancy has a different impact depending on the data rate.

One of the most important challenges facing us today is to personalize services based on user preferences. In order to achieve this objective, the design of Recommender Systems (RSs), which are systems designed to aid the users through different decision-making processes by providing recommendations to them, have been an active area of research. RSs may produce personalized and non-personalized recommendations. Non-personalized RSs provide general suggestions to a user, based on the number of times an item has been selected in the past. Personalized RSs, on the other hand, aim to predict the most suitable items for a specific user, based on the user’s preferences and constraints. The latter are the focus of this thesis. While Recommender Systems have been successful in many domains, a number of challenges remain. For example, most implementations consider only single criteria ratings, and consequently are unable to identify why a user prefers an item over others. Many systems classify the user into one single group or cluster which is an unrealistic approach, since in real world users share commonalities in different degrees with diverse types of users. Others require a large amount of previously gathered data about users’ interactions and preferences, in order to be successfully applied. In this study, we introduce a methodology for the creation of Personalized Multi Criteria Context Aware Recommender Systems that aims to overcome these shortcomings. Our methodology incorporates the user’s current context information, and techniques from the Multiple Criteria Decision Analysis (MCDA) field of study to analyze and model the user preferences. To this end, we create a multi criteria user preference model to assess the utility of each item for a specific user, to then recommend the items with the highest utility. The criteria considered when creating the user preference model are the user’s location, mobility level and user profile. The latter is obtained by considering the user specific needs, and generalizing the user data from a large scale demographic database. We present a case study where we applied our methodology into PeRS, a personal Recommender System to recommend events that will take place within the Ottawa/Gatineau Region. Furthermore, we conduct an offline experiment performed to evaluate our methodology, as implemented in our case study. From the experimental results we conclude that our RS is capable to accurately narrow down, and identify, the groups from a demographic database where a user may belong, and subsequently generate highly accurate recommendation lists of items that match with his/her preferences. This means that the system has the ability to understand and typify the user. Moreover, the results show that the obtained system accuracy doesn’t depend on the user profile. Therefore, the system is potentially capable to produce equally accurate recommendations for a wide range of the population.

The Internet of Things is an emerging technology where everyday devices with sensing and actuating capabilities are connected to the Internet and seamlessly com- municate with other devices over the network. The proliferation of mobile devices enables access to unprecedented levels of rich information sources. Mobile app cre- ators can leverage this information to create personalized mobile applications. The amount of available mobile apps available for download will increase over time, and thus, accessing and managing apps can become cumbersome. This thesis presents AppXimity, a mobile-app-management that provides personalized app suggestions and recommendations by leveraging user preferences and contextual information to provide relevant apps in a given context. Suggested apps represent a subset of the installed apps that match nearby businesses or have been identified by AppXimity as apps of interest to the user, and recommended apps are those apps that are not installed on the user’s device, but may be of interest to the user, in that location. / Graduate / 0984

Nowadays, an increasing amount of media platforms provide the users with opportunities for sharing their opinions about products, companies or people. In order to support users accessing opinion-based information, and to support engineers building systems that require opinion-aware reasoning, intelligent opinion-aware tools and techniques are needed. This thesis contributes methods and technology for opinion-aware information management from two different perspectives, namely document summarisation and knowledge representation. Document summarisation has been widely investigated as a mean to reduce information overload. This thesis focuses on statistical models for summarisation, with a particular attention to divergence-based models, within the context of opinions. Firstly, topic-based document summarisation is addressed, contributing a study on divergence-based document to summary similarity and the definition of a novel algorithm for summarisation based on sentence removal. Secondly, summarisation models are tailored to opinion-oriented content and shown to be useful also when exploited for different tasks such as sentiment classification. Thirdly, summarisation models are applied to knowledge-oriented data, in order to tackle tasks such as entity summarisation. The comprehensive task addressed is the knowledge-based opinion-aware summarisation of content (free text, facts). This thesis also contributes a broad discussion on knowledge representation of opinions. A thorough study on how to model opinions using traditional techniques, such as Entity-Relationship (ER) modelling, underlines that a high-level, opinion-aware layer of conceptual modelling is useful since it hides away implementation details. A conceptual and logical knowledge representation methodology for modelling opinions is hence proposed, with the purpose of guiding engineers towards the use of best practices during the development of sentiment analysis applications. Specifically, an extension of the traditional ER modelling and the definition of an automatic mapping procedure, to translate opinion-aware components of the conceptual model into a relational model, help achieving a clear separation between conceptual and logical modelling. The mapping procedure yields an automatic and replicable methodology to design applications which require opinion-aware reasoning.

Inter-process communications (IPC) are ubiquitous in today’s software systems, yet they are rarely treated as first-class programming concepts. Implementing crosscutting concerns for message-based IPC are difficult, even using aspect-oriented programming languages (AOPL) such as AspectJ. Many of these challenges are because the context of a communication-related crosscutting concern is often a conversation consisting of message sends and receives. Hence, developers typically have to implement communication protocols manually using primitive operations, such as connect, send, receive, and close. This dissertation describes an extension to AspectJ, called CommJ, with which developers can implement communication-related concerns in cohesive and loosely coupled aspects. It then presents preliminary, but encouraging results from a subsequent study that begin by defining a reuse and maintenance quality model. Subsequently the results show seven different ways in which CommJ can improve the reusability and maintainability of applications requiring network communications.

<p>Today, several tourist attractions use handheld devices that act as tour guides to give the customers an improved experience and better knowledge of the attraction. A graphical user interface on the devices provides the users with information through sound, pictures and video. In order to improve the information delivered to the users, some of these guides are location-aware. However, location-aware tour guides are expensive to develop. They have to be developed tailored for each attraction, which is a time consuming job.</p><p>By having a framework for the development of location-aware tour guides, the tour guides will be both easier and less expensive to develop. In addition, it will be easy to make changes to the guides if necessary.</p><p>This project resulted in the development of a prototype for a framework for location-aware tour guides. The framework consists of three main tools; a Creator Tool, a Statistical Tool and a Runtime System. The Creator Tool is used to create and configure new tour guides. The Statistical Tool is used by the staff of the attraction. It generates statistics based on information stored in a log. The Runtime System is the system that provides the mobile devices information, adjusted to their location during a guided tour. To demonstrate the use of the framework, we have developed two client applications, one for PDAs and the other for cellphones. Both applications are electronically location-aware tour guides made for the Nidaros Cathedral.</p><p>The cellphone application is an innovative application that may result in a tremendous evolvement in the development of cellphone applications. It shows great potentials in the area of location-aware cellphone applications with high accuracy, and can be used not only in tour attractions, but also in several other fields. Thus, the project has gained a great deal of publicity, both from newspapers and television.</p>

Location is a primary cue in many context-aware computing systems, and is often represented as a global coordinate, room number, or Euclidean distance various landmarks. A user?s concept of location, however, is often defined in terms of regions in which common activities occur. We show how to partition a space into such regions based on patterns of observed user location and motion. These regions, which we call activity zones, represent regions of similar user activity, and can be used to trigger application actions, retrieve information based on previous context, and present information to users. We suggest that context-aware applications can benefit from a location representation learned from observing users. We describe an implementation of our system and present two example applications whose behavior is controlled by users? entry, exit, and presence in the zones.

Today, several tourist attractions use handheld devices that act as tour guides to give the customers an improved experience and better knowledge of the attraction. A graphical user interface on the devices provides the users with information through sound, pictures and video. In order to improve the information delivered to the users, some of these guides are location-aware. However, location-aware tour guides are expensive to develop. They have to be developed tailored for each attraction, which is a time consuming job. By having a framework for the development of location-aware tour guides, the tour guides will be both easier and less expensive to develop. In addition, it will be easy to make changes to the guides if necessary. This project resulted in the development of a prototype for a framework for location-aware tour guides. The framework consists of three main tools; a Creator Tool, a Statistical Tool and a Runtime System. The Creator Tool is used to create and configure new tour guides. The Statistical Tool is used by the staff of the attraction. It generates statistics based on information stored in a log. The Runtime System is the system that provides the mobile devices information, adjusted to their location during a guided tour. To demonstrate the use of the framework, we have developed two client applications, one for PDAs and the other for cellphones. Both applications are electronically location-aware tour guides made for the Nidaros Cathedral. The cellphone application is an innovative application that may result in a tremendous evolvement in the development of cellphone applications. It shows great potentials in the area of location-aware cellphone applications with high accuracy, and can be used not only in tour attractions, but also in several other fields. Thus, the project has gained a great deal of publicity, both from newspapers and television.