ODMBP: Behavior Forwarding for Multiple Property Destinations in Mobile Social Networks

Abstract

The smartphones are widely available in recent years. Wireless networks and personalized mobile devices are deeply integrated and embedded in our lives. The behavior based forwarding has become a new transmission paradigm for supporting many novel applications. However, the commodities, services, and individuals usually havemultiple properties of their interests and behaviors. In this paper, we profile thesemultiple properties and propose anOpportunisticDissemination Protocol based onMultiple Behavior Profile, ODMBP, inmobile social networks.We firstmap the interest space to the behavior space and extract the multiple behavior profiles from the behavior space.Then, we propose the correlation computing model based on the principle of BM25 to calculate the correlation metric of multiple behavior profiles. The correlation metric is used to forward the message to the users who are more similar to the target in our protocol. ODMBP consists of three stages: user initialization, gradient ascent, and group spread. Through extensive simulations, we demonstrate that the proposed multiple behavior profile and correlation computing model are correct and efficient. Compared to other classical routing protocols, ODMBP can significantly improve the performance in the aspect of delivery ratio, delay, and overhead ratio.