People like us: a social-based service discovery protocol for smart environments

This work proposes an efficient proactive service discovery protocol that leverages the social behavior and the mobility of the people. The protocol is based on the concept that the service discovery performance is strongly affected by the mobility of the users and by their behavior along the time. Indeed, people generally have significant contacts with others like themselves with similar interests, hence they could be interested on similar services. We present simulation results that show that our protocol achieves increased efficiency in discovering services (compared to traditional broadcast-based mechanisms) by efficiently using bandwidth, thus decreasing the energy consumption.