Abstract: Service discovery is an essential task in pervasive computing environments. Simple and efficient service discovery enables heterogeneous and ubiquitous computing devices and services to be easier to use. Service integration uses services as building blocks to achieve complex services. We describe service discovery and service integration, analyze design issues, and categorize the service discovery protocols. Keywords: Service Discovery, Service Integration, Service Security. In 1991, Mark Weiser coined the term ubiquitous computing, which is also called pervasive computing. In pervasive computing environments, people are surrounded by a variety of computing devices. Those devices communicate with each other and provide information “at a glance ” without our “active attention ” [1]. Presently, PCs, notebooks, cell phones, and Personal Data Assistants (PDAs) surround us. In the near future, additional networked computers, ranging from tiny sensors to extremely dynamic and powerful devices will provide a variety of information and services. It becomes overwhelming to manage these devices, configure different kinds of applications, and dynamically find the available computing services in such pervasive computing environments. Service discovery protocols enable computers to be easier to use. They facilitate interaction between

Abstract. We present our results of the conceptual design and the implementation of ubiquitous computing applications using smart identification technologies. First, we describe such technologies and their potential application areas, then give an overview of some of the applications we have developed. Based on the experience we have gained from developing these systems, we point out design concepts that we have found useful for structuring and implementing such applications. Building upon these concepts, we have created two frameworks based on Jini (i.e., distributed Java objects) and Web Services to support the development of ubiquitous computing applications that make use of smart identification technology. We describe our prototype frameworks, discuss the underlying concepts and present some lessons learned.

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Abstract. A motivation behind much UbiComp research has been to make our lives convenient, comfortable and informed, following in the footsteps of Weiser’s calm computing vision. Three themes that have dominated are context awareness, ambient intelligence and monitoring/tracking. While these avenues of research have been fruitful their accomplishments do not match up to anything like Weiser’s world. This paper discusses why this is so and argues that is time for a change of direction in the field. An alternative agenda is outlined that focuses on engaging rather than calming people. Humans are very resourceful at exploiting their environments and extending their capabilities using existing strategies and tools. I describe how pervasive technologies can be added to the mix, outlining three areas of practice where there is much potential for professionals and laypeople alike to combine, adapt and use them in creative and constructive ways.

In pervasive computing environments, powerful handheld devices with wireless connections create opportunities for many new nomadic applications. We propose a new service discovery model, called Splendor, supporting nomadic users and services in public environments. Splendor emphasizes security and supports privacy. Location awareness is integrated for location dependent services discovery and is used to lessen service discovery network infrastructure requirements. We analyze the Splendor system performance and provide our experimental results. 1.

We present a unified model of everyday privacy in ubiquitous computing environments, designed to aid system designers and administrators in conceptualizing the end-user privacy experience. The model accounts for the influence of societal-scale forces, contextual factors, and subjective perception on end-user privacy. We identify notice and consent as the fair information practices of greatest everyday utility to users, as they gradually engender the user's conceptual model of ubicomp privacy. Navigating the regular deluge of personal information collection events in ubicomp requires that notice be minimally intrusive and consent be implicitly granted by a persistent, situationspecific set of user preferences. We extend our model into an interactional metaphor called situational faces, designed to mitigate the complexity of privacy for the end-user. When encountering a situation, a user engages the appropriate face, a metaphorical abstraction of a set of privacy preferences.

The requirement for spontaneous interaction in ubiquitous computing creates security issues over and above those present in other areas of computing, deeming traditional approaches ine#ective. As a result, to support secure collaborations entities must implement selfprotective measures. Trust management is a solution well suited to this task as reasoning about future interactions is based on the outcome of past ones. This requires monitoring of interactions as they take place.

Ubiquitous computing introduces unique requirements for discovery technologies, which let services and devices become aware of each other without explicit human administration.

The vision of ubiquitous computing is becoming a reality thanks to the advent of portable devices and the advances in wireless networking technologies. It aims to facilitate user tasks through seamless utilization of services available in the surrounding environments. In such distributed environments featuring openness, interactions, especially service provision and consumption, between entities that are unknown or barely known to each other, are commonplace. Trust management through reputation mechanism to facilitate such interactions is recognized as an important element of ubiquitous computing. It is, however, faced by the problems of how to stimulate reputation information sharing and honest recommendation elicitation. We present in this paper an incentive compatible reputation mechanism to facilitate the trustworthiness evaluation in ubiquitous computing environments. It is based on probability theory and supports reputation evolution and propagation. Our reputation mechanism not only shows robustness against lies, but also stimulates honest and active recommendations. The latter is realized by ensuring that active and honest recommenders, compared to inactive or dishonest ones, can elicit the most honest (helpful) recommendations and thus suffer the least number of wrong trust decisions, as validated by simulation based evaluation. 1

This paper describes an ongoing investigation into the trust and security concerns of users who carry out interactions in mobile and ubiquitous computing environments. The study is motivated by future scenarios in which it is envisioned that people may be able to spontaneously make their personal, mobile devices interact with other devices in such environments—environments which may be