Context-aware and automatic configuration of mobile devices in cloud-enabled ubiquitous computing

This is the author's accepted manuscript. The final publication is available at Springer via http://dx.doi.org/10.1007/s00779-013-0698-3. Copyright @ Springer-Verlag London 2013.Context-sensitive (or aware) applications have, in recent years, moved from the realm of possibilities to that of ubiquity. One exciting research area that is still very much in the realm of possibilities is that of cloud computing, and in this paper, we present our work, which explores the overlap of these two research areas. Accordingly, this paper explores the notion of cross-source integration of cloud-based, context-aware information in ubiquitous computing through a developed prototypical solution. Moreover, the described solution incorporates remote and automatic configuration of Android smartphones and advances the research area of context-aware information by harvesting information from several sources to build a rich foundation on which algorithms for context-aware computation can be based. Evaluation results show the viability of integrating and tailoring contextual information to provide users with timely, relevant and adapted application behaviour and content

DOBBS: Towards a Comprehensive Dataset to Study the Browsing Behavior of Online Users

The investigation of the browsing behavior of users provides useful information to optimize web site design, web browser design, search engines offerings, and online advertisement. This has been a topic of active research since the Web started and a large body of work exists. However, new online services as well as advances in Web and mobile technologies clearly changed the meaning behind "browsing the Web" and require a fresh look at the problem and research, specifically in respect to whether the used models are still appropriate. Platforms such as YouTube, Netflix or last.fm have started to replace the traditional media channels (cinema, television, radio) and media distribution formats (CD, DVD, Blu-ray). Social networks (e.g., Facebook) and platforms for browser games attracted whole new, particularly less tech-savvy audiences. Furthermore, advances in mobile technologies and devices made browsing "on-the-move" the norm and changed the user behavior as in the mobile case browsing is often being influenced by the user's location and context in the physical world. Commonly used datasets, such as web server access logs or search engines transaction logs, are inherently not capable of capturing the browsing behavior of users in all these facets. DOBBS (DERI Online Behavior Study) is an effort to create such a dataset in a non-intrusive, completely anonymous and privacy-preserving way. To this end, DOBBS provides a browser add-on that users can install, which keeps track of their browsing behavior (e.g., how much time they spent on the Web, how long they stay on a website, how often they visit a website, how they use their browser, etc.). In this paper, we outline the motivation behind DOBBS, describe the add-on and captured data in detail, and present some first results to highlight the strengths of DOBBS

Ten Years of Rich Internet Applications: A Systematic Mapping Study, and Beyond

BACKGROUND: The term Rich Internet Applications (RIAs) is generally associated with Web appli- cations that provide the features and functionality of traditional desktop applications. Ten years after the introduction of the term, an ample amount of research has been carried out to study various aspects of RIAs. It has thus become essential to summarize this research and provide an adequate overview. OBJECTIVE: The objective of our study is to assemble, classify and analyze all RIA research performed in the scienti c community, thus providing a consolidated overview thereof, and to identify well-established topics, trends and open research issues. Additionally, we provide a qualitative discussion of the most inter- esting ndings. This work therefore serves as a reference work for beginning and established RIA researchers alike, as well as for industrial actors that need an introduction in the eld, or seek pointers to (a speci c subset of) the state-of-the-art. METHOD: A systematic mapping study is performed in order to identify all RIA-related publications, de ne a classi cation scheme, and categorize, analyze, and discuss the identi ed research according to it. RESULTS: Our source identi cation phase resulted in 133 relevant, peer-reviewed publications, published between 2002 and 2011 in a wide variety of venues. They were subsequently classi ed according to four facets: development activity, research topic, contribution type and research type. Pie, stacked bar and bubble charts were used to visualize and analyze the results. A deeper analysis is provided for the most interesting and/or remarkable results. CONCLUSION: Analysis of the results shows that, although the RIA term was coined in 2002, the rst RIA-related research appeared in 2004. From 2007 there was a signi cant increase in research activity, peaking in 2009 and decreasing to pre-2009 levels afterwards. All development phases are covered in the identi ed research, with emphasis on \design" (33%) and \implementation" (29%). The majority of research proposes a \method" (44%), followed by \model" (22%), \methodology" (18%) and \tools" (16%); no publications in the category \metrics" were found. The preponderant research topic is \models, methods and methodologies" (23%) and to a lesser extent, \usability & accessibility" and \user interface" (11% each). On the other hand, the topic \localization, internationalization & multi-linguality" received no attention at all, and topics such as \deep web" (under 1%), \business processing", \usage analysis", \data management", \quality & metrics", (all under 2%), \semantics" and \performance" (slightly above 2%) received very few attention. Finally, there is a large majority of \solution proposals" (66%), few \evaluation research" (14%) and even fewer \validation" (6%), although the latter are increasing in recent years

Usability, Efficiency and Security of Personal Computing Technologies

New personal computing technologies such as smartphones and personal fitness trackers are widely integrated into user lifestyles. Users possess a wide range of skills, attributes and backgrounds. It is important to understand user technology practices to ensure that new designs are usable and productive. Conversely, it is important to leverage our understanding of user characteristics to optimize new technology efficiency and effectiveness. Our work initially focused on studying older users, and personal fitness tracker users. We applied the insights from these investigations to develop new techniques improving user security protections, computational efficiency, and also enhancing the user experience. We offer that by increasing the usability, efficiency and security of personal computing technology, users will enjoy greater privacy protections along with experiencing greater enjoyment of their personal computing devices. Our first project resulted in an improved authentication system for older users based on familiar facial images. Our investigation revealed that older users are often challenged by traditional text passwords, resulting in decreased technology use or less than optimal password practices. Our graphical password-based system relies on memorable images from the user\u27s personal past history. Our usability study demonstrated that this system was easy to use, enjoyable, and fast. We show that this technique is extendable to smartphones. Personal fitness trackers are very popular devices, often worn by users all day. Our personal fitness tracker investigation provides the first quantitative baseline of usage patterns with this device. By exploring public data, real-world user motivations, reliability concerns, activity levels, and fitness-related socialization patterns were discerned. This knowledge lends insight to active user practices. Personal user movement data is captured by sensors, then analyzed to provide benefits to the user. The dynamic time warping technique enables comparison of unequal data sequences, and sequences containing events at offset times. Existing techniques target short data sequences. Our Phase-aware Dynamic Time Warping algorithm focuses on a class of sinusoidal user movement patterns, resulting in improved efficiency over existing methods. Lastly, we address user data privacy concerns in an environment where user data is increasingly flowing to manufacturer remote cloud servers for analysis. Our secure computation technique protects the user\u27s privacy while data is in transit and while resident on cloud computing resources. Our technique also protects important data on cloud servers from exposure to individual users

NoiseSPY: a real-time mobile phone platform for urban noise monitoring and mapping

In this paper we present the design, implementation, evaluation, and user experiences of the NoiseSpy application, our sound sensing system that turns the mobile phone into a low-cost data logger for monitoring environmental noise. It allows users to explore a city area while collaboratively visualizing noise levels in real-time. The software combines the sound levels with GPS data in order to generate a map of sound levels that were encountered during a journey. We report early findings from the trials which have been carried out by cycling couriers who were given Nokia mobile phones equipped with the NoiseSpy software to collect noise data around Cambridge city. Indications are that, not only is the functionality of this personal environmental sensing tool engaging for users, but aspects such as personalization of data, contextual information, and reflection upon both the data and its collection, are important factors in obtaining and retaining their interest