Indoor positioning systems that make use of received signal strength based location fingerprints and existing wireless local area network infrastructure have recently been the focus for supporting location-based services in indoor and campus areas. A knowledge and understanding of the properties of the location fingerprint can assist in improving design of algorithms and deployment of position location systems. However, most existing research work ignores the radio signal properties. This paper investigates the properties of the received signal strength reported by IEEE 802.11b wireless network interface cards. Analyses of the data are performed to understand the underlying features of location fingerprints. The performance of an indoor positioning system in terms of its precision is compared using measured data and a Gaussian model to see how closely a Gaussian model may fit the measured data.

A continuous nearest neighbor (CNN) search retrieves the nearest neighbors corresponding to every point in a given query line segment. It is important for location-based services such as vehicular navigation tools and tourist guides. It is infeasible to answer a CNN search by issuing a traditional nearest neighbor query at every point of the line segment due to the large number of queries generated and the large overhead on bandwidth. Algorithms have been proposed recently to support CNN search in the traditional client-server service model. In this paper, we conduct a pioneering study on CNN search in wireless data broadcast environments. We propose two air indexing techniques, namely, R-tree air index and Hilbert curve air index, and develop algorithms based on these two techniques to search CNNs on the air. A simulation is conducted to compare the proposed air indexing techniques with a naive broadcast approach. The result shows that both of the proposed methods outperform the naive approach significantly. The Hilbert Curve air index is superior for uniform data distributions, while the R-tree air index is a better choice for skewed data distributions.

Caching techniques have been successfully employed to overcome some of the problems posed by disconnection and/or limited bandwidth in mobile environments. Demand driven and prefetching techniques to maintain optimal caches have been found to have limited success in such environments. We develop profile based methods to maintain and enhance data availability at mobile client's caches. Profiling techniques determine data items to be prefetched and cached depending on a user group and context. We have developed a prototype system that demonstrates the applicability of the proposed scheme in a crisis management situation. Results of implementation of the above technique in experimental mobile environments show that profile based caching can significantly enhance data availability in mobile and ubiquitous environments.

Recent advances in wireless technology allow Java-enabled devices, such as Smart Phones and PDAs, to create mobile ad hoc networks, over which distributed applications can be executed. Although Java shields the programmers from the heterogeneity of the hardware platforms, a common middleware architecture is needed to support a cooperative execution environment in these networks. In this paper, we present a portable runtime system for smart messages (SMs), a middleware architecture based on execution migration, that we designed and implemented on top of an unmodified Java virtual machine. To facilitate portability, we have designed a lightweight migration mechanism based on Java bytecode instrumentation. This mechanism is suitable for mobile ad hoc networks where limited bandwidth and mobility impose constraints on the amount of data transferred. The experimental results for applications executed over wireless networks of HP iPAQs demonstrate the feasibility of our portable runtime system.

Vision-based user interfaces are a feasible and advantageous modality for wearable computers. To substantiate this claim, we present a robust real-time hand gesture recognition system that is capable of being the sole input provider for a demonstration application. It achieves usability and interactivity even when both the head-worn camera and the object of interest are in motion. We describe a set of general gesture-based interaction styles and explore their characteristics in terms of task suitability and the computer vision algorithms required for their recognition. Preliminary evaluation of our prototype system leads to the conclusion that vision-based interfaces have achieved the maturity necessary to help overcome some limitations of more traditional mobile user interfaces.

Task computing ([R. Masuoka et al., (2003)]) enables a user to compose and execute complex tasks in application-, device- and service-rich environments. Task computing is possible through the availability of semantically described services that, can be composed on-the-fly by end-users into executable tasks. Through the use of a task computing client, users can not only compose tasks from available semantically described services, but discover, create, manage and manipulate services as well. The focus of this paper is the technologies used for dynamic service discovery, and creation, management and manipulation of semantically described services.

In wearable computing environments, a user brings and uses his/her own computer to acquire various services wherever he/she goes. This type of computer, which acts as a service platform for wearable computing, needs autonomy and simplicity of services, flexibility of services/devices configuration, and power saving functions. Since most conventional wearable computing systems do not fulfil all of these requirements, we propose A-WEAR, which is a rule-based wearable computing system. We employ an event-driven rule as a behavior description language of A-WEAR to achieve autonomy and simplicity. Furthermore, we employ a plug-in mechanism to achieve flexibility and power saving. Using our system, we can easily provide and use various services for wearable computing environments.

This work presents an architecture and a proof of concept implementation of a security infrastructure for mobile devices in an infrastructure based pervasive environment. The security infrastructure primarily consists of two parts, the policy engine and the policy enforcement mechanism. Each mobile device within a pervasive environment is equipped with its own policy enforcement mechanism and is responsible for protecting its resources. A mobile device consults the nearest policy server, notifies its current state including its present user, network presence, other accessible devices and location information if available. Using this information the policy server queries the "Rei" engine to dynamically create a policy certificate and issues it to the requesting device. The system wide policy is described in a semantic language "Rei", a lightweight and extensible language which is able to express comprehensive policies using domain specific information. The "Rei" policy engine is able to dynamically decide what rights, prohibitions, obligations, dispensations an actor has on the domain actions. A policy certificate is created and issued to the device. The policy certificate contains a set of granted permissions and a validity period and scope within which the permissions are valid. The policy certificate can be revoked by the policy enforcer based on expiration of the validity period or a combination of timeout, loss of contact with an assigned network. X.509 based public key infrastructure is used to provide identification and authentication.

Ambient intelligence, distributed agent systems, smart buildings and other emerging architectures leave the user lost between large amounts of autonomous entities or agents. With agents in cars, personal devices and other mobile systems, the set of agents available to the user can change rapidly, adding to the problems. We propose a set of agent relations to organize agents in an ad hoc situation. There are dynamic task-, location- and user relations, creating multiple relation hierarchies in agent space. These hierarchies allow robust, space- and task limited, context-sensitive search through agent space. We show how to use this structure to keep user interfaces near the user, and how it can be used to support the user in finding the agent he needs in a context-sensitive way.

We motivate a context fusion network (CFN), an infrastructure model that allows context-aware applications to select distributed data sources and compose them with customized data-fusion operators into a directed acyclic information fusion graph. Such a graph represents how an application computes high-level understandings of its execution context from low-level sensory data. Multiple graphs by different applications interconnect with each other to form a global graph. A key advantage of a CFN is reusability, both at code-level and instance-level, facilitated by operator composition. We designed and implemented a distributed CFN system, Solar, which maps the logical operator graph representation onto a set of overlay hosts. In particular, Solar meets the challenges inherent to heterogeneous and volatile ubicomp environments. By abstracting most complexities into the infrastructure, Solar facilitates both the development and deployment of context-aware applications. We present the operator composition model, basic services of the Solar overlay network, and programming support for the developers. We also discuss some applications built with Solar and the lessons we learned from our experience.