Abstract
Tumblr is a popular microblogging platform that allows users to share content and interact with other users. This paper focuses on the measurement and modeling of Tumblr network traffic characteristics, since few studies have focused on Tumblr from this perspective. Our work uses a combination of active and passive approaches to network traffic measurement. Using Wireshark and mitmproxy, we identify the primary hosts associated with Tumblr traffic, the traffic patterns associated with specific user actions, and the TCP connection behaviour. We then study Tumblr usage by our campus community for one week, using passively collected connection summaries. As a frame of reference, we also compare this traffic with several other popular social media platforms with user-generated content, namely Facebook, Instagram, and Twitter. Our work identifies several similarities and differences in the network traffic patterns for these social networking sites. We also develop and calibrate a synthetic workload model for Tumblr network traffic.
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Notes
- 1.
Our network traffic monitor is restarted every 3Â h to reduce the risks of data loss.
- 2.
We ignore the Oath and Verizon/ANS servers, which contribute negligibly to the connection count and data volume in the empirical Tumblr traffic.
References
Alrajebah, N.: Investigating the structural characteristics of cascades on tumblr. In: Proceedings of IEEE/ACM International Conference on Advances in Social Network Analysis and Mining (ASONAM), Paris, France, pp. 910–917 (2015)
Arlitt, M., Williamson, C.: A synthetic workload model for internet mosaic traffic. In: Proceedings of the 1995 Summer Computer Simulation Conference, Ottawa, ON, Canada, pp. 852–857 (1995)
Benevenuto, F., Rodrigues, T., Cha, M., Almeida, V.: Characterizing user behavior in online social networks. In: Proceedings of the 9th ACM Internet Measurement Conference (IMC), Chicago, IL, pp. 49–62 (2009)
Chang, Y., Tang, L., Inagaki, Y., Liu, Y.: What is tumblr: a statistical overview and comparison. ACM SIGKDD Explor. Newslett. 16(1), 21–29 (2014)
Deng, Q., Li, Z., Wu, Q., Xu, C., Xie, G.: An empirical study of the wechat mobile instant messaging service. In: IEEE INFOCOM Workshops, Atlanta, USA, pp. 390–395, May 2017
Instagram. A quick walk through our history as a company, March 2019. https://instagram-press.com/our-story
Klenow, S., Williamson, C., Arlitt, M., Keshvadi, S.: Campus-level instagram traffic: a case study. In: Proceedings of IEEE International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS), Rennes, France, pp. 228–234 (2019)
Maia, M., Almeida, J., Almeida, V.: Identifying user behavior in online social networks. In: Proceedings of 1st Workshop on Social Network Systems, Glasgow, Scotland, pp. 1–6 (2008)
Mislove, A., Marcon, M., Gummadi, K., Druschel, P., Bhattacharjee, B.: Measurement and analysis of online social networks. In: Proceedings of ACM Internet Measurement Conference (IMC), San Diego, CA, pp. 29–42 (2007)
Mitmproxy (2020). https://www.mitmproxy.org
Paxson, V.: Bro: a system for detecting network intruders in real time. Comput. Netw. 31(23–24), 2435–2463 (1999)
Roy, S., Williamson, C., Mclean, R.: LMS performance issues: a case study of D2L. ISCA Int. J. Comput. Appl. 25(3), 113–122 (2018)
Schneider, F., Feldmann, A., Krishnamurthy, B., Willinger, W.: Understanding online social network usage from a network perspective. In: Proceedings of ACM Internet Measurement Conference (IMC), Chicago, IL, pp. 35–48 (2009)
Tumblr. About, May 2020. https://www.tumblr.com/about
Wikipedia. Tumblr, May 2020. https://en.wikipedia.org/wiki/Tumblr
Wikipedia. Instagram, May 2020. https://en.wikipedia.org/wiki/Instagram
Williamson, C.: Internet traffic measurement. IEEE Internet Comput. 5(6), 70–74 (2001)
Wireshark (2020). https://www.wireshark.org
XKit (2020). https://new-xkit-extension.tumblr.com
Xu, J., Compton, R., Lu, T., Allen, D.: Rolling through tumblr: characterizing behavioral patterns of the microblogging platform. In: Proceedings of ACM Conference on Web Science, Bloomington, IN, pp. 13–22, June 2014
Acknowledgements
The authors thank the anonymous reviewers from IEEE MASCOTS 2020 for their constructive feedback and suggestions on an earlier version of this paper. Financial support for this research was provided in part by the Department of Computer Science at the University of Calgary, and by Canada’s Natural Sciences and Engineering Research Council (NSERC). The authors are also grateful to University of Calgary Information Technologies (UCIT) for facilitating our collection and analysis of the campus-level network traffic.
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Mclean, R., Karamollahi, M., Williamson, C. (2021). Measurement and Modeling of Tumblr Traffic. In: Calzarossa, M.C., Gelenbe, E., Grochla, K., Lent, R., Czachórski, T. (eds) Modelling, Analysis, and Simulation of Computer and Telecommunication Systems. MASCOTS 2020. Lecture Notes in Computer Science(), vol 12527. Springer, Cham. https://doi.org/10.1007/978-3-030-68110-4_16
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