HLSaaS: High-Level Video Streaming as a Service Mohsen - - PowerPoint PPT Presentation

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HLSaaS: High-Level Video Streaming as a Service Mohsen - - PowerPoint PPT Presentation

Sep 01, 2022 147 likes •408 views

HLSaaS: High-Level Video Streaming as a Service Mohsen Amini-Salehi, Xiangbo Li High Performance and Cloud Computing (HPCC) Lab. University of Louisiana at Lafayette 1 Streaming Providers Video Streams Client Devices 2 Video streaming

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HLSaaS: High-Level Video Streaming as a Service

Mohsen Amini-Salehi, Xiangbo Li

High Performance and Cloud Computing (HPCC) Lab. University of Louisiana at Lafayette

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Video Streams Streaming Providers Client Devices

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  • Video streaming constitutes

approximately 64% of all the U.S. Internet traffic in 2014 [1].

  • Cisco estimates that the

streaming traffic will increase to 80% by 2019 [2].

[1] G. I. P. Report, “https://www.sandvine.com/trends/global-internet-phenomena/,” accessed Oct. 1, 2015. [2] C. V. N. Index, “Forecast and methodology, 2014-2019,” 2015.

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Basic Video Streaming: Video On-Demand vs Live-Streaming

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Video On Demand (VOD) Live Streaming

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High-Level Video Streaming Services: Viewer Requirements

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  • Alice wants to remove the inappropriate

contents from videos dynamically for her kids!

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High-Level Video Streaming Services: Publisher Requirements

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  • Bob wants to blur accidentally captured entities

in the video

  • Bob wants to watermark videos with his

company logo

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High-Level Video Streaming Services: Streaming provider requirements

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  • Convert (transcode) videos based on the client

devices characteristics

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Challenges in Providing High-Level Video Streaming

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  • Video processing is computationally

expensive

  • Video processing has to be done in a real-

time manner

  • To address these challenges stream providers

are becoming reliant on cloud services

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  • Storage solutions
  • Hardware failover
  • Networking infrastructure
  • Video contents
  • Customer experience

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Challenges in Utilizing Clouds

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  • Minimum cost while maintaining QoS
  • What are the QoS demands?
  • 1. No delay in the stream (minimum drop rate)
  • Video processing task should complete within

individual deadlines

  • In live streaming missing deadline dropped
  • 2. Minimum start up delay
  • Users judge the quality based on the startup delay
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HLSaaS Architecture

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  • Accepts any high-level video processing request
  • It allocates resources from cloud

– Based on the requested high-level video processing service – Based on the workload

  • Maintains QoS
  • Incurs minimum cost to the provider
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Structure of Video Streams

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  • Videos are streamed as

a sequence of segments

  • Group Of Pictures (GOP)
  • The unit we consider for

processing

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HLSaaS Architecture

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Estimate GOP processing time QoS-aware Scheduling method

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HLSaaS Architecture

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Elasticity Manager QoS and cost aware

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Work Completed*: On-Demand Transcoding of Video Streams

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  • Focusing on the stream provider request
  • Video transcoding:

– Converting the video stream to match the characteristics of client devices

  • Examples: resolution, codec, bit-rate, frame rate

* CVSS: Cost-efficient and and QoD-aware Video Streaming Using Cloud Services, Accepted in IEEE/ACM CCGrid ’16 conference

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Netflix Solution for Transcoding: Pre-Transcode

16 http://techblog.netflix.com/2012/12/videos-of-netflix-talks-at-aws-reinvent.html

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Long Tail Property of Video Streaming

  • We do not need to pre-transcode all videos
  • Pre-transcode just for the “trendy” videos

– The rest can be transcoded “lazily”!

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Trendy videos

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HLSaaS Architecture

QoS-Aware Scheduling Method Dynamic cost- efficient provisioning policy

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QoS-Aware Scheduling Method

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Step1: Search for the shortest completion time VM. Step2: Insert GOP from startup queue in front of the GOP in the batch queue. Step3: Check if the GOP in the batch queue will miss deadline or not.

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Dynamic Cost-Efficient Provisioning Policy

I. Periodic Provisioning Policy α < deadline miss rate < β

  • II. Remedial Provisioning Policy
  • We quickly determine the workload intensity using

startup queue

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 Our dynamic system keeps the QoS violation constantly low and Stable in compare with static method. Our method save the cost when the system is not oversubscribed.

Performance Evaluation

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Future Directions

  • 1. Different video types have affinities with various

services offered by cloud providers

– Creating a heterogeneous VM cluster!

  • 2. Mixing the idea of HLSaaS with Content Delivery

Networks (CDN)

  • 3. Support live streaming and VOD in one system

– Schedule within a single pool of tasks

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Questions?

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Thank You!

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