Distributed Context Monitoring for the Adaptation of Continuous Services

This paper describes a middleware designed for distributed context acquisition and reconciliation intended to support the adaptation of continuous Internet services, like e.g., multimedia streaming. These services persist in time, and are characterized by multiple transmissions of data by the service provider, as a result of a single request from the user. Adapting these services to the current context requires the continuous monitoring of context data, and a real-time adjustment of the adaptation parameters upon the detection of a relevant context change. The proposed solution is based on asynchronous context change notifications, and specific techniques have been designed to minimize the number of unnecessary updates and the re-evaluation of policies. The paper also provides experimental results obtained by developing an adaptive video streaming system and running it on top of the proposed middleware.     

A multi-agent based user context Bayesian neural network analysis system

The increasing user mobility demands placed upon IT services necessitates an environment that enables users to access optimal services at any time and in any place. This study presents research conducted to develop a system that is capable of analyzing user IT service patterns and tendencies and provides the necessary service resources by sharing each user’s context information. First, each user’s context information is gathered to provide the multi-agent software training data necessary to describe user operations in a hybrid peer-to-peer (P2P) structured communication environment. Next, the data collected about each user’s mobile device is analyzed through a Bayesian based neural network system to identify the user’s tendency and extract essential service information. This information provides a communication configuration allowing the user access to the best communication service between the user’s mobile device and the local server at any time and in any place, thereby enhancing the ubiquitous computing environment.     

Adaptation of robot’s perception of fuzzy linguistic information by evaluating vocal cues for controlling a robot manipulator

This article proposes a method for adapting a robot’s perception of fuzzy linguistic information by evaluating vocal cues. The robot’s perception of fuzzy linguistic information such as “very little” depends on the environmental arrangements and the user’s expectations. Therefore, the robot’s perception of the corresponding environment is modified by acquiring the user’s perception through vocal cues. Fuzzy linguistic information related to primitive movements is evaluated by a behavior evaluation network (BEN). A vocal cue evaluation system (VCES) is used to evaluate the vocal cues for modifying the BEN. The user’s satisfactory level for the robot’s movements and the user’s willingness to change the robot’s perception are identified based on a series of vocal cues to improve the adaptation process. A situation of cooperative rearrangement of the user’s working space is used to illustrate the proposed system by a PA-10 robot manipulator.     

Rapid behavior adaptation for human-centered robots in a dynamic environment based on the integration of primitive confidences on multi-sensor elements

This article presents a method for tele-operated mobile robots to rapidly adapt to behavior policies. Since real-time adaptation requires frequent observations of sensors and the behavior of users, rapid policy adaptation cannot be achieved when significant data are not differentiated from insignificant data in every process cycle. Our method solves this problem by evaluating the significance of data for learning based on changes in the degree of confidence. A small change in the degree of confidence can be regarded as reflecting insignificant data for learning (that data can be discarded). Accordingly, the system can avoid having to store experience data too frequently, and the robot can adapt more rapidly to changes in the user’s policy. In this article, we confirm that by taking advantage of a significance evaluation not only of proposition of behavior, but also of each proposition of each piece of sensor-level data, a robot can rapidly adapt to a user’s policy. We discuss the results of two experiments in static and dynamic environments, in both of which the user switched policies between “avoid” and “approach.”     

Visual Grid Workflow in Triana

In this paper, we describe the graphical abstractions for Grids and services that have been implemented within the Triana problem solving environment. We provide an overview of the ways in which Triana interacts with services (e.g., Web and P2P services) and then how we interact with core Grid components, such as resource managers and data management systems through the extensive use of the GridLab GAT interface. We describe in detail the GAT philosophy and implementation and then show how the various GAT primitives can be represented in an intuitive fashion within a Triana workflow. This approach, which we refer to as the Visual GAT, differs substantially from other approaches because we do not tie our implementation to any specific underlying Grid middleware technologies; rather, we base our implementation on application level requirements and model such primitives from a user’s perspective by hiding as much complexity as possible without undermining the core capabilities required. We provide a use case to demonstrate the Visual GAT implementation and show how legacy applications can seamlessly be distributed and integrated in a dynamic fashion within complex data-driven workflow scenarios.     

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.     

Formation conditions of mutual adaptation in human-agent collaborative interaction

When an adaptive agent works with a human user in a collaborative task, in order to enable flexible instructions to be issued by ordinary people, it is believed that a mutual adaptation phenomenon can enable the agent to handle flexible mapping relations between the human user’s instructions and the agent’s actions. To elucidate the conditions required to induce the mutual adaptation phenomenon, we designed an appropriate experimental environment called “WAITER” (Waiter Agent Interactive Training Experimental Restaurant) and conducted two experiments in this environment. The experimental results suggest that the proposed conditions can induce the mutual adaptation phenomenon.     

The Well Mannered Wearable Computer

In this paper we describe continuing work being carried out as part of the Bristol Wearable Computing Initiative. We are interested in the use of context sensors to improve the usefulness of wearable computers. A CyberJacket incorporating a Tourist Guide application has been built, and we have experimented with location and movement sensing devices to improve its performance. In particular, we have researched processing techniques for data from accelerometers which enable the wearable computer to determine the user’s activity. We have experimented with, and review, techniques already employed by others; and then propose new methods for analysing the data delivered by these devices. We try to minimise the number of devices needed, and use a single X-Y accelerometer device. Using our techniques we have adapted our CyberJacket and Tourist Guide to include a multimedia presentation which gives the user information using different media depending on the user’s activity as well as location.     

Using ubiquitous computing in interactive mobile marketing

Unique features of handheld devices, including their mobility, personalization and location-awareness engender new types of applications for mobile commerce, such as mobile advertising. Mobile marketing and advertising applications deliver promotional information to consumers based on their preferences and location. In this paper, we present SMMART, a context-aware, adaptive and personalized m-commerce application designed to deliver targeted promotions to the users of mobile devices about the products they like while guarding the users’ identity and protecting them from any unsolicited messages. Promotions distributed by SMMART are personalized by performing intelligent matching of the user’s shopping interests to current promotions available at a retail site. SMMART can adapt to changing preferences of its user by inconspicuously monitoring his or her shopping habits. We describe a fully functional prototype of SMMART built for Pocket PCs running Windows CE with .NET Compact Framework. This paper also presents a study demonstrating end-user usability and economic viability of SMMART.     

An integrated runtime QoS-aware middleware framework for distributed multimedia applications

Future-generation distributed multimedia applications are expected to be highly scalable to a wide variety of heterogeneous devices, and highly adaptive across wide-area distributed environments. This demands multiple stages of run-time support in QoS-aware middleware architectures, particularly, probing the performance of QoS parameters, instantiating the initial component configurations, and adapting to on-the-fly variations. However, few of the past experiences in related work have shown comprehensive run-time support in all of the above stages – they often design and build a middleware framework by focusing on only one of the run-time issues. In this paper, we argue that distributed multimedia applications need effective run-time middleware support in all these stages to be highly scalable and adaptive across a wide variety of execution environments. Nevertheless, the design of such a middleware framework should be kept as streamlined and simple as possible, leading to a novel and integrated run-time middleware platform to unify the probing, instantiation and adaptation stages. In addition, for each stage, the framework should enable the interaction of peer middleware components across host boundaries, so that the corresponding middleware function can be performed in a coordinated and coherent fashion. We present the design of such an integrated architecture, with a case study to illustrate how it is simple yet effective to monitor and configure complex multimedia applications.     

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.     

Adaptation and user expertise modelling in AthosMail

This article describes the User Model component of AthosMail, a speech-based interactive e-mail application developed in the context of the EU project DUMAS. The focus is on the system’s adaptive capabilities and user expertise modelling, exemplified through the User Model parameters dealing with initiative and explicitness of the system responses. The purpose of the conducted research was to investigate how the users could interact with a system in a more natural way, and the two aspects that mainly influence the system’s interaction capabilities, and thus the naturalness of the dialogue as a whole, are considered to be the dialogue control and the amount of information provided to the user. The User Model produces recommendations of the system’s appropriate reaction depending on the user’s observed competence level, monitored and computed on the basis of the user’s interaction with the system. The article also discusses methods for the evaluation of adaptive user models and presents results from the AthosMail evaluation.The research was done while the author was affiliated with the University of Art and Design Helsinki as the scientific coordinator of the DUMAS project.     

Autopoiesis, the immune system, and adaptive information filtering

Adaptive information filtering is a challenging and fascinating problem. It requires the adaptation of a representation of a user’s multiple interests to various changes in them. We tackle this dynamic problem with Nootropia, a model inspired by the autopoietic view of the immune system. It is based on a self-organising antibody network that reacts to user feedback in order to define and preserve the user interests. We describe Nootropia in the context of adaptive, content-based document filtering and evaluate it using virtual users. The results demonstrate Nootropia’s ability to adapt to both short-term variations and more radical changes in the user’s interests, and to dynamically control its size and connectivity in the process. Advantages over existing approaches to profile adaptation, such as learning algorithms and evolutionary algorithms are also highlighted.

User—robot personality matching and assistive robot behavior adaptation for post-stroke rehabilitation therapy

This paper describes a hands-off socially assistive therapist robot designed to monitor, assist, encourage, and socially interact with post-stroke users engaged in rehabilitation exercises. We investigate the role of the robot’s personality in the hands-off therapy process, focusing on the relationship between the level of extroversion–introversion of the robot and the user. We also demonstrate a behavior adaptation system capable of adjusting its social interaction parameters (e.g., interaction distances/proxemics, speed, and vocal content) toward customized post-stroke rehabilitation therapy based on the user’s personality traits and task performance. Three validation experiment sets are described. The first maps the user’s extroversion–introversion personality dimension to a spectrum of robot therapy styles that range from challenging to nurturing. The second and the third experiments adjust the personality matching dynamically to adapt the robot’s therapy styles based on user personality and performance. The reported results provide first evidence for user preference for personality matching in the assistive domain and demonstrate how the socially assistive robot’s autonomous behavior adaptation to the user’s personality can result in improved human task performance. This work was supported by USC Women in Science and Engineering (WiSE) Program and the Okawa Foundation.     

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.     

Better Living Through Geometry

Mark Weiser described ubiquitous computing as “invisible, everywhere computing that does not live on a personal device of any sort, but is in the woodwork everywhere”[1]. The EasyLiving project is concerned with development of an architecture and technologies for ubiquitous computing environments that allow the dynamic aggregation of diverse I/O devices into a single coherent user experience. Though the need for research in distributed computing, perception and interfaces is widely recognised, the importance of an explicit geometric world model for enhancing the user’s experience of a ubiquitous computing system has not been well-articulated. This paper describes three scenarios that benefit from geometric context and introduces the EasyLiving Geometric Model.     

Context-dependent awareness support in open collaboration environments

The widespread adoption of online services for performing work, home and leisure tasks enables users to operate in the ubiquitous environment provided by the Internet by managing a possibly high number of parallel (private and shared) activity contexts. The provision of awareness information is a key factor for keeping users up-to-date with what happens around them; e.g., with the operations performed by their collaborators. However, the delivery of notifications describing the occurred events can interrupt the users’ activities, with a possible disruptive effect on their emotional and attentional states. As a possible solution to the trade-off between informing and interrupting users, we defined two context-dependent notification management policies which support the selection of the notifications to be delivered on the basis of the user’s current activities, at different granularity levels: general collaboration context versus task carried out. These policies are offered by the COntext depeNdent awaReness informAtion Delivery (CONRAD) framework. We tested such policies with users by applying them in a collaboration environment that includes a set of largely used Web 2.0 services. The experiments show that our policies reduce the levels of workload on users while supporting an up-to-the-moment understanding of the interaction with their shared contexts. The present paper presents the CONRAD framework and the techniques underlying the proposed notification policies.     

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.     

Supporting Ubiquitous IMS-based Teleconferencing Through Discovery and Composition of IMS and Web Components

Natural communication among people happens in flexible ways and is strongly affected by the users’ situation (such as communication tools available, user’s location, and user’s preferences). This situation or context information is seldom used to initiate communication sessions among users. Current communication systems are indifferent about users’ context, often require time consuming manual configurations and often result in conferencing tools not being easily accessible when needed. This leads to lower adoption of innovative communications services. IMS SIP (IP Multimedia Subsystem, Session Initiation Protocol) sessions allow users to access the session from different points of contact (home, office, etc.), however, IMS still requires a prior knowledge of all SIP components that might be used in a SIP session. Furthermore, IMS makes limited use of context information (mainly user-defined availability). To address these issues our research approach combines techniques from pervasive computing with IMS networking principles to facilitate compositions of communication sessions based on users’ context. We propose a platform and APIs for pervasive application development support to allow greater intelligence in IMS applications. We additionally provide mechanisms for IMS applications to apply their intelligence to the configuration of physical devices and web resources used to set up a conference. The innovations proposed in this paper are: (1) A new standard for intelligent IMS-based conferencing applications. (2) Application Development Interfaces (APIs) for a platform for pervasive computing. (3) An architecture for a pervasive IMS platform.