Open Access

ARTICLE

SPN-Based Performance Analysis of Multiple Users’ Behaviors for SNS

by Zhiguo Hong^1,*, Yongbin Wang^2,3, Minyong Shi⁴

1 School of Data Science and Media Intelligence, Communication University of China, Beijing, 100024, China
2 Collaborative Innovation Center, Communication University of China, Beijing, 100024, China
3 State Key Laboratory of Media Convergence and Communication, Communication University of China, Beijing, 100024, China
4 School of Computer and Cyber Sciences, Communication University of China, Beijing, 100024, China

* Corresponding Author: Zhiguo Hong. Email:

Journal of Information Hiding and Privacy Protection 2022, 4(1), 1-13. https://doi.org/10.32604/jihpp.2022.026440

Received 27 December 2021; Accepted 29 January 2022; Issue published 17 June 2022

Abstract

With the rapid development of various applications of Information Technology, big data are increasingly generated by social network services (SNS) nowadays. The designers and providers of SNS distribute different client applications for PC, Mobile phone, IPTV etc., so that users can obtain related service via mobile or traditional Internet. Good scalability and considerably short time delay are important indices for evaluating social network systems. As a result, investigating and mining the principle of users’ behaviors is an important issue which can guide service providers to establish optimal systems with SNS. On the basis of analyzing the characteristics of social network system, this paper constructed a Stochastic Petri Net (SPN) model for describing the behaviors of three users for SNS. Moreover, the scalability of users’ behaviors of SNS was studied by extending the SPN model of three users to the one of four users. Furthermore, average time delay was chosen as the performance index to evaluate the performance of these two constructed SPN models with Stochastic Petri Net Package (SPNP) 6.0. For different parameters of number of connections, traffic load and buffer size, various trends and numerical results are derived thereby. The methodology of modeling and simulation in this paper can be further used to study the performance of SNS.

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Keywords

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