Insights from Analysis of Video Streaming Data to Improve Resource Management

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 (ISPs), and Carrier Network Operators, to improve their resource allocation and management techniques.