Our mobile computing devices connect with other devices over proximity networks on a daily basis. Due to the availability of protocols like DLNA, applications in connected devices can enable media sharing experiences where content flows among devices in the proximity space. Despite the pervasiveness of DLNA and other similar implementations, average users perceive these connections to be intrinsically complex. This perception is not limited to media sharing and affects other types of N-device experiences. In this paper we propose to avoid the inherent complexity problem with the design of intelligent contextual systems that respond proactively to user intent. Users should be capable of expressing intent, and connected devices should gain the intelligence necessary to proactively satisfy user intent. We introduce a software service with an inference engine to determine when the contextual conditions are such that user intent can be satisfied. Media sharing connections, content, and protocols are proactively configured based on contextual inference in anticipation of user needs. The system has been designed as an Android service so that any media-sharing application that uses the service becomes contextually proactive.

In today's content-rich homes, people use the television as a primary interface to enjoy various kinds of media, partly due to the screen size of today's TVs and partly due to its central placement in many homes. On the other hand, the Internet has become an immense source of information and entertainment content. A traditional TV viewer's experience can be greatly enhanced by enabling seamless search and access for relevant Internet content on the TV. In this demo, we illustrate a novel system and methodology that enables TV users to access relevant Internet content while watching TV.

The Internet has become an extremely popular source of entertainment and information. But, despite the growing amount of media content, most Web sites today are designed for access via web browsers on the PC, making it difficult for home consumers to access Internet content on their TVs or other devices that lack keyboards. As a result, the Internet is generally restricted to access on the PC or via cumbersome interfaces on non-PC devices. In this paper, we present unobtrusive and assistive technologies enabling home users to easily find and access Internet content related to the TV program they are watching. Using these technologies, the user is now able to access relevant information and video content on the Internet while watching TV.

WSDL provides the potential for Web services to enrich consumers' lives. However, it has had only limited success in enterprise environments and even less in the mass market. Apart from the difficulties and high costs involved in current approaches, another reason is the low precision for Web Services discovery using the most widely known tool: search engines. Seeking for effective ways to change the situation, we conducted an experiment to examine better approaches of using general-purpose search engines to discover Web Services. We used nine different approaches for publishing Web Services and two groups of total 18 queries for retrieving them using Yahoo and Google search engines. The queries were fired to each search engine daily over a week and the top 100 search results returned from every search are collected and analyzed. The results show that for both search engines, embedding a WSDL specification in a Web page that provides semantic description of the service yield the best results.

Current home networking technologies such as UPNP, Jini and HAVi, only focus on connecting devices electronically in a variety of different forms that allow simple device interactions. The result is that devices act in incompatible islands, making their use confusing to users and a nightmare for application developers. To realize a smart home environment, we need to seamlessly integrate devices and services into our every day lives. In this paper, we describe a middleware platform to provide the integration of devices, services and contents in a home. Our middleware facilitates integration of both data (content, preferences, etc.) and applications across home networking technologies to improve consumer and developer usability.

As consumer electronic devices become more powerful and networked, users are required to understand more and more 'complex' device functionalities just to carry out simplest tasks. Users are experiencing more and more inconvenience and frustration as the number and complexity of home devices rise and the amount of content/data stored in the home increases. To address these problems, we have developed middleware technologies to integrate heterogeneous CE devices and allow users to simply select what activities they want to perform in the home. Our middleware software allows users to use a simple pseudo-English interface to achieve home tasks without having to consider where a particular content is located and how to achieve that task.

It is widely understood that most system downtime is accounted for by programming errors and administration time. However, a growing body of work has indicated an increasing cause of downtime may stem from transient errors in computer system hardware due to external factors, such as cosmic rays. This work indicates that moving to denser semiconductor technologies at lower voltages has the potential to increase these transient errors. In this paper, we investigate the susceptibility of commodity operating systems and applications on commodity PC processors to these soft-errors and we introduce ideas regarding the improved recovery from these transient errors in software. Our results indicate that, for the Linux kernel and a Java virtual machine running sample workloads, many errors are not activated, mostly due to overwriting. In addition, given current and upcoming microprocessor support, our results indicate that those errors activated, which would normally lead to system reboot, need not be fatal to the system if software knowledge is used for simple software recovery. Together, they indicate the benefits of simple memory soft error recovery handling in commodity processors and software.

Pervasive computing allows a user to access an application on heterogeneous devices continuously and consistently. However it is challenging to deliver complex applications on resource-constrained mobile devices, such as cellular telephones and PDA. Different approaches, such as application-based or system-based adaptations, have been proposed to address the problem. However existing solutions often require degrading application fidelity. We believe that this problem can be overcome by dynamically partitioning the application and offloading part of the application execution to a powerful nearby surrogate. This will enable pervasive application delivery to be realized without significant fidelity degradation or expensive application rewriting. Because pervasive computing environments are highly dynamic, the runtime offloading system needs to adapt to both application execution patterns and resource fluctuations. Using the fuzzy control model, we have developed an offloading inference engine to adaptively solve two key decision-making problems during runtime offloading: (1) timely triggering of adaptive offloading, and (2) intelligent selection of an application partitioning policy. Extensive trace-driven evaluations show the effectiveness of the offloading inference engine.

Many visions of the future predict a world with pervasive computing, where computing services and resources permeate the environment. In these visions, people will want to execute a service on any available device without worrying about whether the service has been tailored for the device. We believe that it will be difficult to create services that can execute well on the wide variety of devices that are being developed because of problems with diversity and resource constraints. We believe that these problems can be greatly reduced by using an ad-hoc distributed platform to transparently off-load portions of a service from a resource-constrained device to a nearby server. We implemented a preliminary prototype and emulator to study this approach. Our experiments show the beneficial use of nearby resources to relieve both memory and processing constraints, when it is appropriate to do so. We believe that this approach will reduce the burden on developers by masking more device details.