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The industry is producing new wireless mobile devices, such as smart phones, at an ever increasing pace. In terms of processors and memory, these devices are as powerful as the PCs were one decade ago. Therefore, they are perfectly suitable to become the first real-life platforms for ubiquitous computing. For instance, they can be programmed to run location-aware applications that provide people with real-time information relevant to their current places. Deploying such applications in our daily life, however, requires a good understanding of their power requirements in order to ensure that mobile devices can indeed support them. This paper presents a quantitative analysis of power consumption for location-aware applications in our SmartCampus project, which builds a large scale test-bed for mobile social computing. Based on this analysis, we conclude that carefully designed applications can run for up to six hours, while updating the user location frequently enough to support real-time location-aware communication.

Review of the literature suggests seven fundamental privacy challenges in the domain of ubiquitous social computing. To date, most research in this area has focused on the features associated with the revelation of personal location data. However, a more holistic view of privacy concerns that acknowledges these seven risks is required if we are to deploy privacy respecting next generation social computing applications. We highlight the threat associated with user inferences made possible by knowledge of the context and use of social ties. We also describe work in progress to both understand user perceptions and build a privacy sensitive urban enclave social computing system.

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