Optimal Harmonization of Out-Network Traffic Control Regulations in Social Networks

Asefeh Asemi1, Abu Bakar Munir2, Ali Alibeigi3, Adeleh Asemi4

Abstract – Regulations of use of social networks, as one of the key components in these networks, serve an important role in controlling the flow of traffic. The study of the harmonization of these terms and regulations can be a significant step to avoid congestion and (Users’) rejection in the network. Harmonization of traffic control regulations (TCR) among social networks is one of the best solutions to establish consequent traffic flow out of the network. Depending on the conditions, harmonization can be done in different ways. This article examines the direct pass and indirect pass methods. Node phase differences are key elements for harmonization of social networks considered in this review. To calculate the optimal phasing and appropriate phase difference, first the status of a user in the two social network samples has been analyzed using Gephi software, and then the results have been simulated by charting. In this article, the harmonization of traffic control regulations (TCR) was done based on evaluation of the TCR performance through determining the appropriate phase differences and reference rule and calculating the measurement of Latency (LT) in the main network port. This latency was calculated as the difference of the expected time and real time of connection or login to the network in simulated conditions. The achieved results indicate that in unsaturated conditions using indirect pass method and in saturated conditions, due to rejection of user and inability of network TCR, using indirect pass method is the best choice for harmonization of the TCR among social networks.

Keywords – Social networks, Harmonization, Regulation, Traffic, Facebook, LinkedIn, Node, Gephi, Rejection, Latency.

1 Associate Professor, University of Isfahan, Iran (Corresponding Author)
2 Professor, Faculty of Law, University of Malaya (UM), Malaysia,
3 PhD Std. Faculty of Law, University of Malaya (UM) Malaysia,
4 PhD Std. FSKTM, Dept. of AI, University of Malaya (UM) Malaysia,

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