Identify & Measure Social Relations: Routing Algorithm Based on Social Relations in Opportunistic Networks

Abstract

Identify & measure social relations has been proposed as a method for information routing in opportunistic networks. In this paper, we design a social-relations-based routing algorithm (SRBRA), which overcomes the common issues in existing identify &measure social relation algorithms, such as the deficiency of measuring parameters and the restrict usage of application domain. Firstly, by analyzing the real-time data from mobile nodes in the network, we summarize and extract factors that affect social relations between these mobile nodes. Then make inference and evaluation for the complexity and dynamic of these factors from multiple angles, calculate the social-relations values between each sensor node from these factors. Finally, based on the values of social relations, we sort out the network topology information of the neighbors, and select the best nest hop relay node for information routing. Simulation experiments show that SRBRA is cost effective and has high delivery ratio.