Name
Abstract | ||
|---|---|---|
Instagram is a popular network application for photo sharing, video streaming, and online social media interaction. In this paper, we present results from an initial characterization study of Instagram network traffic, as viewed from a large campus edge network. Despite the challenges of NAT, DHCP, end-to-end encryption, and high traffic volume, we are able to identify key characteristics of Instagram traffic, which exceeds 1 TB per day. The main highlights from our study include classic observations such as diurnal usage patterns, Zipf-like distributions for IP frequency-rank profile, and heavy-tailed transfer size distributions. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/MASCOTS.2019.00032 | 2019 IEEE 27th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS) |
Keywords | Field | DocType |
Network traffic measurement,Internet traffic characterization,Online social networks,Instagram,TCP/IP | Computer science,Multimedia,Distributed computing | Conference |
ISSN | ISBN | Citations |
2375-0227 | 978-1-7281-4950-9 | 0 |
PageRank | References | Authors |
0.34 | 17 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Steffen Berg Klenow | 1 | 0 | 0.34 |
| C. Williamson | 2 | 2998 | 417.38 |
| Martin F. Arlitt | 3 | 0 | 0.34 |
| Sina Keshvadi | 4 | 0 | 1.35 |