Performance Analysis of Video On-demand and Live Video Streaming using Cloud based Services

Abstract

The advent of Cyber-Physical Systems (CPS) has brought a revolutionary change coined as a mixture of information, communication, computation, and control. With applications in smart grid, health monitoring, automatic avionics, distributed robotics, etc., CPS is currently an area of attention among the academia and industry. The advancement of mobile communications and embedded technology has made it possible to build large scale CPS consisting of the interconnection of mobile phones. These devices collect information about the surrounding environment at any time anywhere basis through real-time video capture. Video streaming has proven to be a massive industry that is growing rapidly playing an important role in everyday life. Customer-driven approach wanting best experience with quality has to be the core offering of contemporary scenario. Video streaming is categorized into Video-On-Demand Streaming (VoDS) and Live Video Streaming (LVS) showing the current state-of-art opportunities. Many diverse applications of video streaming are military video surveillance using drones, live sports match player face recognition, on-demand video characters recognition, movie summarization like identifying parts of the movie which are viewed many times by different users, movie and series recognition, motion detection, gesture recognition, image segmentation, etc. This paper introduces an approach to develop video analysis on VoD and LVS using cloud-based services and analyzes the impact of Quality of Experience (QoE), cost, and bandwidth on the cloud. To achieve the best user experience for video streaming and video analysis, Content Delivery Network (CDN) offers the best QoE at various analyzed locations using various cloud providers like Amazon Web Services (AWS) CloudFront, Google Cloud CDN, Azure CDN, Akamai CDN, etc.