R-SOR: Ranked Social-based Routing Protocol in Opportunistic Mobile Social Networks


  • M. Alrfaay Common First Year Deanship, Jouf University, Saudi Arabia
  • A. K. Ali Faculty of Computer Science and Information Technology, Universiti Malaysia Sarawak, Malaysia
  • S. Chaoui College of Computer and Information Sciences, Jouf University, Saudi Arabia
  • H. Lenando Faculty of Computer Science and Information Technology, Universiti Malaysia Sarawak, Malaysia
  • S. Alanazi College of Computer and Information Sciences, Jouf University, Saudi Arabia
Volume: 12 | Issue: 1 | Pages: 7998-8006 | February 2022 | https://doi.org/10.48084/etasr.4612


Exploiting social information to improve routing performance is an increasing trend in Opportunistic Mobile Social Networks (OMSNs). Selecting the next message’s relay node based on the user’s social behavior is a critical factor in attaining a high delivery rate. So, to ascertain the most efficient selection of the next relay, the correlation between daily social activities and the social characteristics in the user profiles can be exploited. In this paper, we consider the impact of the social characteristics on mobile user activities during certain periods of the day and then rank these characteristics based on their relative importance in order to be included in the routing protocol. These processes consolidate the proposed Ranked Social-based Routing (R-SOR) protocol to provide an effective way for data dissemination in OMSN. We use the real data set INFOCOM06 to evaluate the proposed protocol. The experimental results show that the proposed protocol has higher routing efficiency than flooding-based protocols such as Epsoc and Epidemic, prediction-based protocols such as PRoPHET, and social-based protocols such as MSM and Bubble Rap.


opportunistic networks, mobile social networks, data dissemination, social-based routing


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How to Cite

M. Alrfaay, A. K. Ali, S. Chaoui, H. Lenando, and S. Alanazi, “R-SOR: Ranked Social-based Routing Protocol in Opportunistic Mobile Social Networks”, Eng. Technol. Appl. Sci. Res., vol. 12, no. 1, pp. 7998–8006, Feb. 2022.


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