From pervasive to social computing
Sonia Ben Mokhtar, Licia Capra · 2009
Pervasive Social Computing is becoming the incontrovertible evolution of pervasive computing, thanks to the pervasiveness of handheld devices and the enormous popularity of social networking websites. Moving away from the traditional human-device interaction paradigm, Pervasive Social Computing aims to take advantage of human social relationships, expressed as social networks, to enable the fulfilment of users' tasks on the move, ultimately promoting social interactivity. In order to realise this new vision, we present in this paper a model for the semantic specification of users' tasks, along with a set of algorithms for matching these specifications based on users' social preferences. Our model is based on the FOAF (Friend Of A Friend) ontology in order to support the semantic specification and reasoning on user social preferences and tasks. Using a variety of real social networking datasets, we analyse strengths and limitations of the various algorithms in terms of users' satisfaction, computational complexity and run-time overhead. We wrap up these algorithms into a Pervasive Social Computing middleware, and investigate the impact of alternative architectural deployments using different campus-based mobility traces, both in terms of users' satisfaction and communication overhead. Our thorough evaluation provides guidelines for the development of future Pervasive Social Computing applications, both in terms of matching and deployment strategies.