MIMOSA: context-aware adaptation for ubiquitous web access

The ubiquitous computing scenario is characterized by heterogeneity of devices used to access services, and by frequent changes in the user’s context. Hence, adaptation according to the user’s context and the used devices is necessary to allow mobile users to efficiently exploit Internet-based services. In this paper, we present a distributed framework, named MIMOSA, that couples a middleware for context-awareness with an intermediary-based architecture for content adaptation. MIMOSA provides an effective and efficient solution for the adaptation of Internet services on the basis of a comprehensive notion of context, by means of techniques for aggregating context data from distributed sources, deriving complex contextual situations from raw sensor data, evaluating adaptation policies, and solving possible conflicts. The middleware allows programmers to modularly build complex adaptive services starting from simple ones, and includes tools for assisting the user in declaring her preferences, as well as mechanisms for detecting incorrect system behaviors due to a wrong choice of adaptation policies. The effectiveness and efficiency of MIMOSA are shown through the development of a prototype adaptive service, and by extensive experimental evaluations.     

Discovering frequent user--environment interactions in intelligent environments

Intelligent Environments are expected to act proactively, anticipating the user’s needs and preferences. To do that, the environment must somehow obtain knowledge of those need and preferences, but unlike current computing systems, in Intelligent Environments, the user ideally should be released from the burden of providing information or programming any device as much as possible. Therefore, automated learning of a user’s most common behaviors becomes an important step towards allowing an environment to provide highly personalized services. In this article, we present a system that takes information collected by sensors as a starting point and then discovers frequent relationships between actions carried out by the user. The algorithm developed to discover such patterns is supported by a language to represent those patterns and a system of interaction that provides the user the option to fine tune their preferences in a natural way, just by speaking to the system.     

Design and implementation of a smart system for personalization and accurate selection of mobile services

Wireless mobile services are computing applications that run on handheld wireless devices. Such applications must work within the daunting constraints of the devices, which include memory, processing power, input capabilities, and size of display. It is therefore important that mobile services take into account the user’s context, optimize resource usage, and minimize input effort imposed on the user. In this paper, we present the design and implementation of a smart agent-enabled system for personalizing wireless mobile services and advertisements for Java 2 Micro Edition (J2ME) or Java ME, and Wireless Application Protocol (WAP) enabled devices. We use software agents for context filtering because such autonomous software entities have characteristics that can benefit mobile devices and the wireless environment, and the Composite Capability/Preference Profiles (CC/PP) standard for defining profiles for user preferences and device capabilities. The system incorporates the use of artificial neural networks to adaptively and iteratively learn to select the best available service based on contextual information. The system is evaluated using practical operating scenarios, as well as empirical data and results show an 87% success rate in the selection of the best available service.     

Spatial cloaking for anonymous location-based services in mobile peer-to-peer environments

This paper tackles a privacy breach in current location-based services (LBS) where mobile users have to report their exact location information to an LBS provider in order to obtain their desired services. For example, a user who wants to issue a query asking about her nearest gas station has to report her exact location to an LBS provider. However, many recent research efforts have indicated that revealing private location information to potentially untrusted LBS providers may lead to major privacy breaches. To preserve user location privacy, spatial cloaking is the most commonly used privacy-enhancing technique in LBS. The basic idea of the spatial cloaking technique is to blur a user’s exact location into a cloaked area that satisfies the user specified privacy requirements. Unfortunately, existing spatial cloaking algorithms designed for LBS rely on fixed communication infrastructure, e.g., base stations, and centralized/distributed servers. Thus, these algorithms cannot be applied to a mobile peer-to-peer (P2P) environment where mobile users can only communicate with other peers through P2P multi-hop routing without any support of fixed communication infrastructure or servers. In this paper, we propose a spatial cloaking algorithm for mobile P2P environments. As mobile P2P environments have many unique limitations, e.g., user mobility, limited transmission range, multi-hop communication, scarce communication resources, and network partitions, we propose three key features to enhance our algorithm: (1) An information sharing scheme enables mobile users to share their gathered peer location information to reduce communication overhead; (2) A historical location scheme allows mobile users to utilize stale peer location information to overcome the network partition problem; and (3) A cloaked area adjustment scheme guarantees that our spatial cloaking algorithm is free from a “center-of-cloaked-area” privacy attack. Experimental results show that our P2P spatial cloaking algorithm is scalable while guaranteeing the user’s location privacy protection.     

Supporting device discovery and spontaneous interaction with spatial references

The RELATE interaction model is designed to support spontaneous interaction of mobile users with devices and services in their environment. The model is based on spatial references that capture the spatial relationship of a user’s device with other co-located devices. Spatial references are obtained by relative position sensing and integrated in the mobile user interface to spatially visualize the arrangement of discovered devices, and to provide direct access for interaction across devices. In this paper we discuss two prototype systems demonstrating the utility of the model in collaborative and mobile settings, and present a study on usability of spatial list and map representations for device selection.     

Protecting location privacy in mobile geoservices using fuzzy inference systems

Mobile geoservices, especially location-based services (LBSs), are becoming more popular each day. The most important goal of these services is to use a user’s location to provide location-aware services. Because the user’s spatial information can be abused by organizations or advertisers, and sometimes for criminal purposes, the protection of this information is a necessary part of such services. There has been substantial research on privacy protection in LBSs and mobile geoservices; most studies have attempted to anonymize the user and hide his/her identity or to engage the user in the protection process. The major defects of these previous approaches include an increased complexity of system architecture, a decrease in service capabilities, undesirable processing times, and a failure to satisfy users. Additionally, anonymization is not a suitable solution for context-aware services. Therefore, in this paper, a new approach is proposed to locate users with different levels of spatial precision, based on his/her spatio-temporal context and a user’s group, through fuzzy inference systems. The user’s location and the time of the request determine the spatio-temporal context of the user. A fuzzy rule base is formed separately for each group of users and services. An interview is a simple method to extract the rules. The spatial precision of a user’s location, which is obtained from a fuzzy system, goes to a spatial function called the conceptualization function, to determine the user’s location based on one of the following five levels of qualitative precision: geometrical coordinates, streets, parish, region, and qualitative location, such as the eastern part of the city. Thus, there is no need to anonymize users in mobile geoservices or to turn the service off. The applicability and efficiency of the proposed method are shown for a group of taxi drivers.     

Transaction pseudonyms in mobile environments

Network Operators start to offer formerly hidden services such as location service, messaging services and presence services. This fosters the development of a new class of innovative context aware applications that are operated by third party application providers. However, without the implementation of proper privacy protection mechanisms, location and presence information, that is processed by third party application providers, may also imply severe risks to users. If no privacy protection is foreseen, the user’s identity could be used maliciously which renders such applications dangerous. To protect the user’s sensitive data such as location information we propose a novel service architecture which fosters the development of innovative applications that brings together internet applications with telco services. An underlying privacy enhancing mechanism that is based on the notion of pseudonyms allows even untrusted third party application providers to access sensitive data provided by telco services such as location, presence or messaging services. Due to their high security, pseudonyms guarantee that the user’s identity is kept secret towards the untrusted application providers. Due to its low computational complexity this pseudonym generation scheme can also be implemented on devices such as mobile phones and digital assistants with only little computational power and restricted memory capabilities. To illustrate our approach, we demonstrate a transportation ticket application that implements the proposed service architecture. This application allows the use of transportation tickets which are extended by the location-tracking functionality. Similar to the well known paper based transportation tickets our solution supports anonymity of users even if the ticket application “knows” the location of the holder. Oliver Jorns is a researcher at the Telecommunications Research Center in Vienna and is also a Lecturer at the University of Vienna. Oliver Jung is employed as a Senior Researcher at the Telecommunications Research Center Vienna. He is also member of ISO/IEC JTC1 SC27 (IT security techniques). Gerald Quirchmayr is Professor at the Institute for Computer Science and Business Informatics at the University of Vienna and since January 2005 he heads the Department of Distributed and Multimedia Systems, Faculty of Computer Science, at the University of Vienna.     

Human-agent service matching using natural language queries: system test and training

Smart environments, ambient intelligence and intelligent agents leave the user lost between large amounts of services. Ad-hoc networks, mobile agents and mobile devices make the set of available services dynamic over time and space, increasing the user’s problems to find the service he needs. Earlier, we presented a ServiceMatcher that can find the agent best fitting to the user’s natural language request. This paper presents performance results of the ServiceMatcher. The test queries come from human users in a realistic scenario (see our other paper in this issue). With a short training of the agent vocabularies, over 80% correct service matches are found.     

Context-driven personalized service discovery in pervasive environments

Pervasive environments are characterized by a large number of embedded devices offering their services to the user. Which of the available services are of most interest to the user considerably depends on the user’s current context. User context is often rich and very dynamic; making an explicit, user-driven discovery of services impractical. Users in such environments would instead like to be continuously informed about services relevant to them. Implicit discovery requests triggered by changes in the context are therefore prevalent. This paper proposes a proactive service discovery approach for pervasive environments addressing these implicit requests. Services and user preferences are described by a formal context model called Hyperspace Analogue to Context, which effectively captures the dynamics of context and the relationship between services and context. Based on the model, we propose a set of algorithms that can continuously present the most relevant services to the user in response to changes of context, services or user preferences. Numeric coding methods are applied to improve the algorithms’ performance. The algorithms are grounded in a context-driven service discovery system that automatically reacts to changes in the environment. New context sources and services can be dynamically integrated into the system. A client for smart phones continuously informs users about the discovery results. Experiments show, that the system can efficiently provide the user with continuous, up-to-date information about the most useful services in real time.     

Adaptive IPTV services based on a novel IP Multimedia Subsystem

Heterogeneous communication devices are emerging and changing the way of communication. Innovative multimedia applications are now accessible through these embedded systems. The 3GPP IP Multimedia Subsystem (IMS) provides a basic architecture framework for the Next Generation Network (NGN) supporting the convergence platform for service provisioning in heterogeneous networks. ETSI TISPAN standardization effort focuses on delivering IPTV services on such platform. Nevertheless, IPTV on IMS standardization suffers from a lack of efficient user-centric network management mechanisms as the end-user may consume IPTV service from different access networks, on different mobile devices, at anytime. User’s Perceived Quality of Service (PQoS) or Quality of Experience (QoE) of IPTV service may also suffer from wireless access network impairments. This paper introduces new functionalities in IPTV over IMS architecture which optimize satisfaction of the end-user and resource utilization of the operator’s networks. A context-sensitive User Profile (UP) model is used to deliver IPTV streams adapted to the user’s environment. In order to optimize the operator network usage, the impact of spatiotemporal dynamics of the video content on the deduced perceptual quality is considered. A Multimedia Content Management System (MCMS) is proposed to perform dynamic cross-layer adaptation of the IPTV stream based on PQoS measurements at the end-user side.     

MASHA: A multi-agent system handling user and device adaptivity of Web sites

A user that navigates on the Web using different devices should be characterized by a global profile, which represents his behaviour when using all these devices. Then, the user’s profile could be usefully exploited when interacting with a site agent that is able to provide useful recommendations on the basis of the user’s interests, on one hand, and to adapt the site presentation to the device currently exploited by the user, on the other hand. However, it is not suitable to construct such a global profile by a software running on the exploited device since this device (e.g., a mobile phone or a palmtop) may have limited resources. Therefore, in this paper, we propose a multi-agent architecture, called MASHA, handling user and device adaptivity of Web sites, in which each device is provided with a client agent that autonomously collects information about the user’s behaviour associated to just that device. However, the user profile contained in this client is continuously updated with information coming from a unique server agent, associated with the user. Such information is collected by the server agent from the different devices exploited by the user, and represents a global user profile. The third component of this architecture, called adapter agent, is capable to generate a personalized representation of the Web site, containing some useful recommendations derived by both an analysis of the user profile and the suggestions coming from other users exploiting the same device.     

A new model for context-aware transactions in mobile services

With the ubiquity of handheld devices (such as smart phones and PDAs) and the availability of a wide range of mobile services (such as mobile banking, road traffic updates, and weather forecast), people can nowadays access information and conduct online transactions virtually anywhere and anytime. In such flexible, dynamic but less reliable environment, transaction management technology is believed to provide service reliability and data consistency. Indeed, in mobile and ubiquitous environments where devices as well as services can seamlessly join and leave the ubiquitous network; transaction management can be very helpful during the recovery of services from failure. Current transaction models and commit protocols do not take into account context information. However, in mobile environments, it is imperative to consider context information in the commit of a transaction—i.e., a transaction can be successfully completed if it meets the required context. In this paper, we propose a new model for context-aware transactions and their performance management in mobile environments. Unlike conventional transactions, context-aware transactions adapt to the required context. By context, we mean the service’s context as well as the users’ context that includes users’ needs and preferences. This paper designs and develops the proposed transaction model and evaluates its performance in terms of time and message complexities as well as transaction’s throughput.     

A calendar based Internet content pre-caching agent for small computing devices

We described in earlier publications the principles of a system where Internet content would be pre-cached, based on contextual information obtained from a user’s electronic calendar. The model for such a system envisioned a set of cooperating agents, distributed on a user’s desktop and mobile device, which would be responsible for making decisions on the context and preferences of the user, and downloading the relevant internet content through a land-based broadband connection and storing it on the mobile device. This paper presents and discusses established pre-caching techniques and their suitability for use on mobile information access scenarios. It proceeds in describing the implementation details of an alternative approach, a calendar-based pre-caching system and presents the findings of tests that were made with human subjects on such a system.

Look, Ma, My homepage is Mobile!

Much of the ongoing research in ubiquitous computing has concentrated on providing context information, e.g. location information, to the level of services and applications. Typically, mobile clients obtain location information from their environment which is used to provide “locally optimal” services. In contrast, it may be of interest to obtain information about the current context a mobile user or device is in, from a client somewhere on the Web, i.e. to use the mobile device as an information provider for Internet clients. As an instance of such services we propose the metaphor of a “location-aware” Web homepage of mobile users providing information about, e.g. the current location a mobile user is at. Requesting this homepage can be as easy as typing a URL containing the mobile user's phone number such ashttp://mhp.net/+49123456789 in an off-the-shelf browser. The homepage is dynamically constructed as Web users access it and it can be configured in various ways that are controlled by the mobile user. We present the architecture and implementation and discuss issues around this example of “inverse” ubiquitous computing.     

The Human Communication Space: Towards I-centric Communications

In the last few years, a variety of concepts for service integration and corresponding systems have been developed. On the one hand, they aim for the interworking and integration of classical telecommunications and data communications services. On the other, they are focusing on universal service access from a variety of end-user systems. Many of the technical problems, resulting from the service integration, and service personalisation have been solved during the last years. However, all these systems are driven by the concept of providing several technologies to users by keeping the peculiarity of each service.  Looking at humans’ communication behaviour and their communication space, it is obvious that human beings interact habitually in a set of contexts with their environment. The individual information preferences and needs, persons to interact with, and the set of devices controlled by each individual define their personal communication space. Following this view, a new approach is to build communication systems not on the basis of specific technologies, but on the analysis of the individual communication spaces. The result is a communication system adapted to the demands of each individual (I-centric). The communication system will act on behalf of users’ demands, reflecting recent actions to enable profiling and self-adaptation to contexts and situations.  In this paper, we introduce I-centric Communications, an approach to design communication systems that adapt themselves to the individual communication space and individual environment and situation. In this context “I” means I, or individual, “Centric” means adaptable to I requirements and a certain user environment.     

Hyperlinking reality via camera phones

A novel user interface concept for camera phones, called “Hyperlinking Reality via Camera Phones”, that we present in this article, provides a solution to one of the main challenges facing mobile user interfaces, that is, the problem of selection and visualization of actions that are relevant to the user in her current context. Instead of typing keywords on a small and inconvenient keypad of a mobile device, a user of our system just snaps a photo of her surroundings and objects in the image become hyperlinks to information. Our method commences by matching a query image to reference panoramas depicting the same scene that were collected and annotated with information beforehand. Once the query image is related to the reference panoramas, we transfer the relevant information from the reference panoramas to the query image. By visualizing the information on the query image and displaying it on the camera phone’s (multi-)touch screen, the query image augmented with hyperlinks allows the user intuitive access to information.     

User-selectable interactive recommendation system in mobile environment

Mobile devices need to provide more accurate and personalized information in a computing environment with a small screen and limited information retrieval functions. This paper presents a user-selectable recommendation system that reflects a user interest group by employing collaborative filtering as technique to provide useful information in a mobile environment. We form similar groups by simultaneously considering a user’s information preferences and demographics. Then we reconstruct lists of a final recommendation based on what search results the similar demographic group has chosen. This is an optional filter for the search results. This means that we provide an interactive flexible recommendation list that considers a user’s intent more actively, rather than unilaterally. We show the Mean Absolute Error result to evaluate the recommendation and finally show the realization of a prototype that is based on both the iPhone and Android phone environments.     

Exploring Issues of User Model Transparency and Proactive Behaviour in an Office Environment Control System

It is important that systems that exhibit proactive behaviour do so in a way that does not surprise or frustrate the user. Consequently, it is desirable for such systems to be both personalised and designed in such a way as to enable the user to scrutinise her user model (part of which should hold the rules describing the behaviour of the system). This article describes on-going work to investigate the design of a prototype system that can learn a given user’s behaviour in an office environment in order to use the inferred rules to populate a user model and support appropriate proactive behaviour (e.g. turning on the user’s fan under appropriate conditions). We explore the tension between user control and proactive services and consider issues related to the design of appropriate transparency with a view to supporting user comprehensibility of system behaviour. To this end, our system enables the user to scrutinise and possibly over-ride the ‘IF-THEN’ rules held in her user model. The system infers these rules from the context history (effectively a data set generated using a variety of sensors) associated with the user by using a fuzzy-decision-tree-based algorithm that can provide a confidence level for each rule in the user model. The evolution of the system has been guided by feedback from a number of real-life users in a university department. A questionnaire study has yielded supplementary results concerning the extent to which the approach taken meets users’ expectations and requirements.     

Mobile access to real-time information—the case of autonomous stock brokering

When services providing real-time information are accessible from mobile devices, functionality is often restricted and no adaptation of the user interface to the mobile device is attempted. Mobile access to real-time information requires designs for multi-device access and automated facilities for the adaptation of user interfaces. We present TapBroker, a push update service that provides mobile and stationary access to information on autonomous agents trading stocks. TapBroker is developed for the Ubiquitous Interactor system and is accessible from Java Swing user interfaces and Web user interfaces on desktop computers, and from a Java Awt user interface on mobile phones. New user interfaces can easily be added without changes in the service logic.     

Toward accessible self-service kiosks through intelligent user interfaces

Public self-service kiosks provide key services such as ticket sales, airport check-in and general information. Such kiosks must be universally designed to be used by society at large, irrespective of the individual users’ physical and cognitive abilities, level of education and familiarity with the system. The noble goal of universal accessibility is hard to achieve. This study reports experiences with a universally designed kiosk prototype based on a multimodal intelligent user interface that adapts to the user’s physical characteristics. The user interacts with the system via a tall rectangular touch-sensitive display where the interaction area is adjusted to fit the user’s height. A digital camera is used to measure the user’s approximate reading distance from the display such that the text size can be adjusted accordingly. The user’s touch target accuracy is measured, and the target sizes are increased for users with motor difficulties. A Byzantine visualization technique is employed to exploit unused and unreachable screen real estate to provide the user with additional visual cues. The techniques explored in this study have potential for most public self-service kiosks.