Content and Context Aware Strategies for QoS Support in VANETs

The increasing interest in autonomous coordinated driving and in proactive safety services, exploiting the wealth of sensing and computing resources which are gradually permeating the urban and vehicular environments, is making provisioning of high levels of QoS in vehicular networks an urgent issue. At the same time, the spreading model of a smart car, with a wealth of infotainment applications, calls for architectures for vehicular communications capable of supporting traffic with a diverse set of performance requirements. So far efforts focused on enabling a single specific QoS level. But the issues of how to support traffic with tight QoS requirements (no packet loss, and delays inferior to 1ms), and of designing a system capable at the same time of efficiently sustaining such traffic together with traffic from infotainment applications, are still open. In this paper we present the approach taken by the CONTACT project to tackle these issues. The goal of the project is to investigate how a VANET architecture, which integrates content-centric networking, software-defined networking, and context aware floating content schemes, can properly support the very diverse set of applications and services currently envisioned for the vehicular environment.

Developing context-aware pervasive computing applications: Models and approach

There is growing interest in the use of context-awareness as a technique for developing pervasive computing applications that are flexible, adaptable, and capable of acting autonomously on behalf of users. However, context-awareness introduces a variety of software engineering challenges. In this paper, we address these challenges by proposing a set of conceptual models designed to support the software engineering process, including context modelling techniques, a preference model for representing context-dependent requirements, and two programming models. We also present a software infrastructure and software engineering process that can be used in conjunction with our models. Finally, we discuss a case study that demonstrates the strengths of our models and software engineering approach with respect to a set of software quality metrics.

Context-aware vertical handovers between WLAN and 3G networks

Vertical handovers can transform heterogeneous networks into an integrated communication environment. Such integration can lead to seamless communication if context information is used to support vertical handovers. Seamless communication environments are needed for future pervasive/ubiquitous systems, which are context aware and can adapt to context changes, including network disconnections, changes in network quality of service and changes in user preferences. This paper describes a generic, context-aware handover solution for multimedia applications and illustrates how this handover works for redirection of communication between WLANs and GPRS or UMTS networks. A description of a prototype for WLAN/GPRS handover and the results of handover experiments are also presented.

Active node supporting context-aware vertical handover in pervasive computing environment with redundant positioning

A major requirement for pervasive systems is to integrate context-awareness to support heterogeneous networks and device technologies and at the same time support application adaptations to suit user activities. However, current infrastructures for pervasive systems are based on centralized architectures which are focused on context support for service adaptations in response to changes in the computing environment or user mobility. In this paper, we propose a hierarchical architecture based on active nodes, which maximizes the computational capabilities of various nodes within the pervasive computing environment, while efficiently gathering and evaluating context information from the user's working environment. The migratable active node architecture employs various decision making processes for evaluating a rich set of context information in order to dynamically allocate active nodes in the working environment, perform application adaptations and predict user mobility. The active node also utilizes the Redundant Positioning System to accurately manage user's mobility. This paper demonstrates the active node capabilities through context-aware vertical handover applications.

Context -aware data caching for mobile computing environments

The deployment of wireless communications coupled with the popularity of portable devices has led to significant research in the area of mobile data caching. Prior research has focused on the development of solutions that allow applications to run in wireless environments using proxy based techniques. Most of these approaches are semantic based and do not provide adequate support for representing the context of a user (i.e., the interpreted human intention.). Although the context may be treated implicitly it is still crucial to data management. In order to address this challenge this dissertation focuses on two characteristics: how to predict (i) the future location of the user and (ii) locations of the fetched data where the queried data item has valid answers. Using this approach, more complete information about the dynamics of an application environment is maintained. ^ The contribution of this dissertation is a novel data caching mechanism for pervasive computing environments that can adapt dynamically to a mobile user's context. In this dissertation, we design and develop a conceptual model and context aware protocols for wireless data caching management. Our replacement policy uses the validity of the data fetched from the server and the neighboring locations to decide which of the cache entries is less likely to be needed in the future, and therefore a good candidate for eviction when cache space is needed. The context aware driven prefetching algorithm exploits the query context to effectively guide the prefetching process. The query context is defined using a mobile user's movement pattern and requested information context. Numerical results and simulations show that the proposed prefetching and replacement policies significantly outperform conventional ones. ^ Anticipated applications of these solutions include biomedical engineering, tele-health, medical information systems and business. ^

Context-aware personalization environment for mobile computing

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Multi-purpose infrastructure for delivering and supporting mobile context-aware applications

The use of contextual information in mobile devices is receiving increasing attention in mobile and ubiquitous computing research. An important requirement for mobile development today is that devices should be able to interact with the context. In this paper we present a series of contributions regarding previous work on context-awareness. In the first place, we describe a client-server architecture that provides a mechanism for preparing target non context-aware applications in order to be delivered as context-aware applications in a semi-automatic way. Secondly, the framework used in the server to instantiate specific components for context-awareness, the Implicit Plasticity Framework, provides independence from the underlying mobile technology used in client device, as it is shown in the case studies presented. Finally, proposed infrastructure deals with the interaction among different context constraints provided by diverse sensors. All of these contributions are extensions to the infrastructure based on the Dichotomic View of plasticity, which now offers multi-purpose support.

Component Architecture for Context-Aware Applications

Mobiililaitteisiin tehdyt sovellukset ovat nykyään laajassa käytössä. Mobiilisovellukset tarjoavat käyttäjälleen usein tietyn ennalta määritellyn toiminnallisuuden eivätkä ne pysty mukautumaan vaihtelevaan käyttöympäristöönsä. Jos sovellus olisi tietoinen käyttöympäristöstään ja sen muutoksista, se voisi tarjota käyttäjälleen tilanteeseen sopivia ominaisuuksia. Käyttöympäristöstään tietoiset hajautetut sovellukset tarvitsevat kuitenkin huomattavasti perinteisiä sovelluksia monimutkaisemman arkkitehtuurin toimiakseen. Tässä työssä esitellään hajautetuille ja kontekstitietoisille sovelluksille tarkoitettu ohjelmistoarkkitehtuuri. Työ perustuu Oulun yliopiston CAPNET-tutkimusprojektissa kehitettyyn, mobiilisovelluksille tarkoitettuun arkkitehtuuriin. Tämän työn tarkoituksena on tarjota ratkaisuja niihin puutteisiin, jotka tulivat esille CAPNET-arkkitehtuurin kehitys- ja testausvaiheessa. Esimerkiksi arkkitehtuurin komponenttien määrittelyä tulisi tarkentaa ja ne tulisi jakaa horisontaalisiin kerroksiin niiden ominaisuuksien ja alustariippuvuuden mukaisesti. Työssä luodaan katsaus olemassa oleviin teknologioihin jotka tukevat hajautettujen ja kontekstitietoisten järjestelmien kehittämistä. Myös niiden soveltumista CAPNET-arkkitehtuuriin analysoidaan. Työssä esitellään CAPNET-arkkitehtuuri ja ehdotetaan uutta arkkitehtuuria ja komponenttien kerrosjaottelua. Ehdotuksessa arkkitehtuurin komponentit ja järjestelmän rakenne määritellään ja mallinnetaan UML-menetelmällä. Työn tuloksena on arkkitehtuurimäärittely, joka jakaa nykyisen arkkitehtuurin komponentit kerroksiin. Komponenttien rajapinnat on määritelty selkeästi ja tarkasti. Työ tarjoaa myös projektiryhmälle hyvän lähtökohdan uuden arkkitehtuurin suunnittelulle ja toteuttamiselle.

Trustworthy context dependency in ubiquitous systems

The modern society is getting increasingly dependent on software applications. These run on processors, use memory and account for controlling functionalities that are often taken for granted. Typically, applications adjust the functionality in response to a certain context that is provided or derived from the informal environment with various qualities. To rigorously model the dependence of an application on a context, the details of the context are abstracted and the environment is assumed stable and fixed. However, in a context-aware ubiquitous computing environment populated by autonomous agents, a context and its quality parameters may change at any time. This raises the need to derive the current context and its qualities at runtime. It also implies that a context is never certain and may be subjective, issues captured by the context’s quality parameter of experience-based trustworthiness. Given this, the research question of this thesis is: In what logical topology and by what means may context provided by autonomous agents be derived and formally modelled to serve the context-awareness requirements of an application? This research question also stipulates that the context derivation needs to incorporate the quality of the context. In this thesis, we focus on the quality of context parameter of trustworthiness based on experiences having a level of certainty and referral experiences, thus making trustworthiness reputation based. Hence, in this thesis we seek a basis on which to reason and analyse the inherently inaccurate context derived by autonomous agents populating a ubiquitous computing environment in order to formally model context-awareness. More specifically, the contribution of this thesis is threefold: (i) we propose a logical topology of context derivation and a method of calculating its trustworthiness, (ii) we provide a general model for storing experiences and (iii) we formalise the dependence between the logical topology of context derivation and its experience-based trustworthiness. These contributions enable abstraction of a context and its quality parameters to a Boolean decision at runtime that may be formally reasoned with. We employ the Action Systems framework for modelling this. The thesis is a compendium of the author’s scientific papers, which are republished in Part II. Part I introduces the field of research by providing the mending elements for the thesis to be a coherent introduction for addressing the research question. In Part I we also review a significant body of related literature in order to better illustrate our contributions to the research field.

Semantic-based middleware solutions to support context-aware service provisioning in pervasive environments

The dynamicity and heterogeneity that characterize pervasive environments raise new challenges in the design of mobile middleware. Pervasive environments are characterized by a significant degree of heterogeneity, variability, and dynamicity that conventional middleware solutions are not able to adequately manage. Originally designed for use in a relatively static context, such middleware systems tend to hide low-level details to provide applications with a transparent view on the underlying execution platform. In mobile environments, however, the context is extremely dynamic and cannot be managed by a priori assumptions. Novel middleware should therefore support mobile computing applications in the task of adapting their behavior to frequent changes in the execution context, that is, it should become context-aware. In particular, this thesis has identified the following key requirements for novel context-aware middleware that existing solutions do not fulfil yet. (i) Middleware solutions should support interoperability between possibly unknown entities by providing expressive representation models that allow to describe interacting entities, their operating conditions and the surrounding world, i.e., their context, according to an unambiguous semantics. (ii) Middleware solutions should support distributed applications in the task of reconfiguring and adapting their behavior/results to ongoing context changes. (iii) Context-aware middleware support should be deployed on heterogeneous devices under variable operating conditions, such as different user needs, application requirements, available connectivity and device computational capabilities, as well as changing environmental conditions. Our main claim is that the adoption of semantic metadata to represent context information and context-dependent adaptation strategies allows to build context-aware middleware suitable for all dynamically available portable devices. Semantic metadata provide powerful knowledge representation means to model even complex context information, and allow to perform automated reasoning to infer additional and/or more complex knowledge from available context data. In addition, we suggest that, by adopting proper configuration and deployment strategies, semantic support features can be provided to differentiated users and devices according to their specific needs and current context. This thesis has investigated novel design guidelines and implementation options for semantic-based context-aware middleware solutions targeted to pervasive environments. These guidelines have been applied to different application areas within pervasive computing that would particularly benefit from the exploitation of context. Common to all applications is the key role of context in enabling mobile users to personalize applications based on their needs and current situation. The main contributions of this thesis are (i) the definition of a metadata model to represent and reason about context, (ii) the definition of a model for the design and development of context-aware middleware based on semantic metadata, (iii) the design of three novel middleware architectures and the development of a prototypal implementation for each of these architectures, and (iv) the proposal of a viable approach to portability issues raised by the adoption of semantic support services in pervasive applications.

Context detection and abstraction in smart environments

Context-aware computing is currently considered the most promising approach to overcome information overload and to speed up access to relevant information and services. Context-awareness may be derived from many sources, including user profile and preferences, network information, sensor analysis; usually context-awareness relies on the ability of computing devices to interact with the physical world, i.e. with the natural and artificial objects hosted within the "environment”. Ideally, context-aware applications should not be intrusive and should be able to react according to user’s context, with minimum user effort. Context is an application dependent multidimensional space and the location is an important part of it since the very beginning. Location can be used to guide applications, in providing information or functions that are most appropriate for a specific position. Hence location systems play a crucial role. There are several technologies and systems for computing location to a vary degree of accuracy and tailored for specific space model, i.e. indoors or outdoors, structured spaces or unstructured spaces. The research challenge faced by this thesis is related to pedestrian positioning in heterogeneous environments. Particularly, the focus will be on pedestrian identification, localization, orientation and activity recognition. This research was mainly carried out within the “mobile and ambient systems” workgroup of EPOCH, a 6FP NoE on the application of ICT to Cultural Heritage. Therefore applications in Cultural Heritage sites were the main target of the context-aware services discussed. Cultural Heritage sites are considered significant test-beds in Context-aware computing for many reasons. For example building a smart environment in museums or in protected sites is a challenging task, because localization and tracking are usually based on technologies that are difficult to hide or harmonize within the environment. Therefore it is expected that the experience made with this research may be useful also in domains other than Cultural Heritage. This work presents three different approaches to the pedestrian identification, positioning and tracking: Pedestrian navigation by means of a wearable inertial sensing platform assisted by the vision based tracking system for initial settings an real-time calibration; Pedestrian navigation by means of a wearable inertial sensing platform augmented with GPS measurements; Pedestrian identification and tracking, combining the vision based tracking system with WiFi localization. The proposed localization systems have been mainly used to enhance Cultural Heritage applications in providing information and services depending on the user’s actual context, in particular depending on the user’s location.

Context Aware e-Learning Objects and their Types from the Perspective of the Object-Oriented Paradigm

The contribution of this article demonstrates how to identify context-aware types of e-Learning objects (eLOs) derived from the subject domains. This perspective is taken from an engineering point of view and is applied during requirements elicitation and analysis relating to present work in constructing an object-oriented (OO), dynamic, and adaptive model to build and deliver packaged e-Learning courses. Consequently, three preliminary subject domains are presented and, as a result, three primitive types of eLOs are posited. These types educed from the subject domains are of structural, conceptual, and granular nature. Structural objects are responsible for the course itself, conceptual objects incorporate adaptive and logical interoperability, while granular objects congregate granular assets. Their differences, interrelationships, and responsibilities are discussed. A major design challenge relates to adaptive behaviour. Future research addresses refinement on the subject domains and adaptive hypermedia systems.

A Model for Proactivity in Mobile, Context-aware Recommender Systems

A proactive recommender system pushes recommendations to the user when the current situation seems appropriate, without explicit user request. This is conceivable in mobile scenarios such as restaurant or gas station recommendations. In this paper, we present a model for proactivity in mobile recommender systems. The model relies on domain-dependent context modeling in several categories. The recommendation process is divided into two phases to first analyze the current situation and then examine the suitability of particular items. We have implemented a prototype gas station recommender and conducted a survey for evaluation. Results showed good correlation of the output of our system with the assessment of users regarding the question when to generate recommendations.