Insights from Analysis of Video Streaming Data to Improve Resource Management
Sabidur Rahman, Hyunsu Muny, Hyongjin Leey, Youngseok Lee, Massimo, Tornatore, and Biswanath Mukherjee

TL;DR
This paper analyzes video streaming data from Korea's largest OTT provider to uncover user behavior patterns, aiding resource management for OTTs, CDNs, ISPs, and carriers.
Contribution
It provides new insights into user demographics, viewing habits, and patterns, informing better resource allocation strategies in video streaming networks.
Findings
Correlation between user profiles and viewing habits
Viewing patterns such as early leaving vs. steady viewing
Device usage and viewing time distributions
Abstract
Today a large portion of Internet traffic is video. Over The Top (OTT) service providers offer video streaming services by creating a large distributed cloud network on top of a physical infrastructure owned by multiple entities. Our study explores insights from video streaming activity by analyzing data collected from Korea's largest OTT service provider. Our analysis of nationwide data shows interesting characteristics of video streaming such as correlation between user profile information (e.g., age, sex) and viewing habits, viewing habits of users (when do the users watch? using which devices?), viewing patterns (early leaving viewer vs. steady viewer), etc. Video on Demand (VoD) streaming involves costly (and often limited) compute, storage, and network resources. Findings from our study will be beneficial for OTTs, Content Delivery Networks (CDNs), Internet Service Providers…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
