The capacity to gather and timely deliver to the service level any relevant information that can characterize the service-provisioning environment, such as computing resources/capabilities, physical device location, user preferences, and time constraints, usually defined as context-awareness, is widely recognized as a core function for the development of modern ubiquitous and mobile systems. Much work has been done to enable context-awareness and to ease the diffusion of context-aware services; at the same time, several middleware solutions have been designed to transparently implement context management and provisioning in the mobile system. However, to the best of our knowledge, an in-depth analysis of the context data distribution, namely, the function in charge of distributing context data to interested entities, is still missing. Starting from the core assumption that only effective and efficient context data distribution can pave the way to the deployment of truly context-aware services, this article aims at putting together current research efforts to derive an original and holistic view of the existing literature. We present a unified architectural model and a new taxonomy for context data distribution by considering and comparing a large number of solutions. Finally, based on our analysis, we draw some of the research challenges still unsolved and identify some possible directions for future work.

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A survey of context data distribution for mobile ubiquitous systems

Recently, we started to experience a shift from physical communities to virtual communities, which leads to missed social opportunities in our daily routine. For instance, we are not aware of neighbors with common interests or nearby events. Mobile social computing applications (MSCAs) promise to improve social connectivity in physical communities by leveraging information about people, social relationships, and places. This article presents MobiSoC, a middleware that enables MSCA development and provides a common platform for capturing, managing, and sharing the social state of physical communities. Additionally, it incorporates algorithms that discover previously unknown emergent geo-social patterns to augment this state. To demonstrate MobiSoC's feasibility, we implemented and tested on smart phones two MSCAs for location-based mobile social matching and place-based ad hoc social collaboration. Experimental results showed that MobiSoC can provide good response time for 1,000 users. We also demonstrated that an adaptive localization scheme and carefully chosen cryptographic methods can significantly reduce the resource consumption associated with the location engine and security on smart phones. A user study of the mobile social matching application proved that geo-social patterns can double the quality of social matches and that people are willing to share their location with MobiSoC in order to benefit from MSCAs.

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MobiSoC: a middleware for mobile social computing applications

In the scope of ubiquitous computing, one of the key issues is the awareness of context, which includes diverse aspects of the user's situation including his activities, physical surroundings, location, emotions and social relations, device and network characteristics and their interaction with each other. This contextual knowledge is typically acquired from physical, virtual or logical sensors. To overcome problems of heterogeneity and hide complexity, a significant number of middleware approaches have been proposed for systematic and coherent access to manifold context parameters. These frameworks deal particularly with context representation, context management and reasoning, i.e. deriving abstract knowledge from raw sensor data. This article surveys not only related work in these three categories but also the required evaluation principles.

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Survey of Context Provisioning Middleware

This paper reconceptualises the role of the small “local” newspaper in a new media environment and argues that definitions and concepts currently used to describe and define such publications are becoming increasingly problematic as newspapers shift into both print and online formats. The paper highlights the continued importance of geography for such newspapers at a time when there is wide academic debate on the relevance of territory and boundaries and the impact of time–space compression in a new media world. It argues, however, that a focus on a newspaper’s geographic connection must also acknowledge the increasing boundlessness and openness of the social space in which a newspaper operates. Ultimately this paper suggests the concept of “geo-social” news may be a more appropriate framework for scholars to consider such publications. I draw on the work of geography scholars, and discussions around “space” and “place” to construct the notion of “geo-social” news, highlighting some exemplars of small com...

BREAKING BOUNDARIES: Recasting the “local” newspaper as “geo-social” news in a digital landscape

Recently, we started to experience a shift from physical communities to virtual communities, which leads to missed social opportunities in our daily routine. For instance, we are not aware of neighbors with common interests or nearby events. Mobile social computing applications (MSCAs) promise to improve social connectivity in physical communities by leveraging information about people, social relationships, and places. This paper presents MobiSoC, a middleware that enables MSCAs development and provides a common platform for capturing, managing, and sharing the social state of physical communities. Additionally, it incorporates algorithms that discover previously unknown emergent geosocial patterns to augment this state. To demonstrate Mo-biSoC's feasibility, we implemented and tested on smart phones two MSCAs for location-based mobile social matching and place-based ad hoc social collaboration.

/pdf/the-mobisoc-middleware-for-mobile-social-computing-2ids0rvhp0.pdf

The MobiSoC middleware for mobile social computing: challenges, design, and early experiences

Mobile locatable devices can help identify previously unknown ad hoc or semi-permanent groups of people and their meeting places. Newly identified groups or places can be recommended to people to enhance their geo-social experience, while respecting privacy constraints. For instance, new students can learn about popular hangouts on campus or faculty members can learn about groups of students routinely having research discussions. This paper presents a clustering algorithm based on user copresence that identifies such groups and places even when group members participate to only a certain fraction of meetings. Simulation results demonstrate that 90 96% of group members can be identified with negligible false positives when the user meeting attendance is at least 50%. Experimental results using one-month of mobility traces collected from smart phones running Intel's PlaceLab location engine successfully identified all groups that met regularly during that period. Additionally, the group places were identified with good accuracy.

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Sanil Paul

Papers

Automatic identification of informal social groups and places for geo-social recommendations