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SCALABLE VIDEO CODING IN CONTENT -A WARE NETWORKS Michael Grafl Institute of Information Technology Alpen-Adria Universität Klagenfurt, Austria Michael Grafl 1 Scalable Video Coding in Content-Aware Networks COMET-ENVISION workshop on Future Media Distribution Networks Nov. 10-11 2011, Slough, UK
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Page 1: C -A N - COMET Project

SCALABLE VIDEO CODING IN

CONTENT-AWARE NETWORKS

Michael Grafl Institute of Information Technology

Alpen-Adria Universität Klagenfurt, Austria

Michael Grafl 1 Scalable Video Coding in Content-Aware Networks

COMET-ENVISION workshop on Future Media Distribution Networks

Nov. 10-11 2011, Slough, UK

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OUTLINE Introduction

ALICANTE Project Overview

Conceptual Architecture

Comparison to ICN

Use Cases for SVC in CAN (Analysis wrt. ICN research challenges) Unicast

Multicast

P2P Streaming

Web/HTTP Streaming

Step-by-Step Walkthrough

Conclusions

Michael Grafl Scalable Video Coding in Content-Aware Networks 2

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INTRODUCTION Information-Centric Networking (ICN) Revolutionary approach

Content-Aware Networking (CAN) Evolutionary approach

ALICANTE project

Scalable Video Coding (SVC) Extension of H.264/MPEG-4 AVC

Spatial, temporal and quality (SNR) scalability

Base layer + multiple enhancement layers

Coding overhead: ~ 10% wrt. H.264

Michael Grafl Scalable Video Coding in Content-Aware Networks 3

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ALICANTE Project Info: EU FP7-ICT project

Duration: March 2010 – Aug 2013

20 partners

"Media Ecosystem Deployment through Ubiquitous Content-Aware Network Environments"

Goal: New Home-Box layer and CAN layer with distributed cross-layer adaptation and universal multimedia access enabling cooperation between providers, operators, and end-users

Michael Grafl Scalable Video Coding in Content-Aware Networks 4

http://ict-alicante.eu

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Michael Grafl Scalable Video Coding in Content-Aware Networks 5

CAN CAN

CAN CAN

CAN CAN

MANE MANE

MANE MANE

Physical Layer: autonomous systems

CAN Layer: in-network components as overlay

Home-Box Layer HB Layer: networked components as overlay HB

HB HB HB

HB

User Environment Context-

aware

Content-aware

Network-aware

AS AS AS

Service Environment: content and services

User Environment: devices and end user

Service Environment

Network Environment

ALICANTE CONCEPTUAL ARCHITECTURE

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ALICANTE VS. FULL ICN APPROACH

Michael Grafl Scalable Video Coding in Content-Aware Networks 6

Degree of awareness on upper

layer information at network level

Approaches:

Best effort

QoS-based virtual splitting

Content-aware networks

Content-type awareness

Service-aware networking

Full ICN

Content/object awareness

Name/location resolution,

routing of requests,

caching at network nodes

ALICANTE

approach

Evolutionary approach for FI

(Mid-way to full ICN)

Caching and storage

In Home-Boxes (network edge)

and Content Servers

Scalable and Cost-Efficient

Content Distribution

Name/location resolution –

at Service level (not in routers)

Content-awareness

aggregated CA and associated

processing at network level

Deployment

Seamless/incremental deployment

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USE CASES FOR SVC IN CAN Role of scalable media formats for enabling

content-aware networking

Unicast, Multicast, Peer-to-Peer Streaming,

Web/HTTP Streaming

Analysis wrt. ICN research challenges:

Routing & Forwarding

Caching & Buffering

Quality of Service/Experience (QoS/QoE)

Michael Grafl Scalable Video Coding in Content-Aware Networks 7

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SYSTEM OVERVIEW FOR USE CASES

Michael Grafl Scalable Video Coding in Content-Aware Networks 8

ICNN2

Buffer Buffer

ICNN1

SVC-Base Layer Enhancement Layer 1 Enhancement Layer 2

U1

U2

U3 Full-HD TV

R1

R3

R2

S1

S2

HD-Ready TV

Mobile

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USE CASES: UNICAST Example: Video on Demand (VoD)

RTP (with SST of SVC) and RTSP

Routing & Forwarding: ICN node can react to network fluctuations

• In-network adaptation of SVC at ICN node (for short-term fluctuations)

• Signal to sender for dropping SVC layers (for long-term fluctuations)

Caching & Buffering: ICN node can perform prefix caching

• Reduce start-up delay

• Selective caching of SVC layers

QoS/QoE: (applies to all use cases) Consider terminal capabilities when requesting SVC layers

Monitor network conditions at ICN nodes (cf. ALICANTE)

Smooth, undistorted playout

Michael Grafl Scalable Video Coding in Content-Aware Networks 9

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USE CASES: MULTICAST Receiver-Driven Layered Multicast (RDLM) of SVC

RTP in MST mode (each SVC layer in own session)

Routing & Forwarding:

ICN nodes adapt to network conditions through subscription

to SVC layers

ICN nodes as bridges between native and overlay multicast

(ALICANTE: virtual content-aware network of ICN nodes)

Selective treatment of SVC layers (MPLS, DiffServ)

Caching & Buffering:

Prefix caching to reduce start-up delay in non-live scenarios

Michael Grafl Scalable Video Coding in Content-Aware Networks 10

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USE CASES: P2P STREAMING Receivers request pieces from multiple senders

P2P network as overlay

Receiver only requests SVC layers supported by end-user terminal

Routing & Forwarding: ICN nodes can act as peers, forming an in-network

overlay

Caching & Buffering: Aggregate requests and perform information-centric

buffering (during sliding window) at ICN nodes

Michael Grafl Scalable Video Coding in Content-Aware Networks 11

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USE CASES: WEB/HTTP STREAMING Download via HTTP (partial) GET requests

Content fragmented into segments (e.g., per SVC layer and GOP)

Manifest file describes structure of segments and available representations

Standard: Dynamic Adaptive Streaming over HTTP (DASH)

Overcome NAT traversal & firewall issues

Stateless sender

Unicast, multicast, and multisource (P2P-like) scenarios

Routing & Forwarding: ICN node signals network condition to receiver (implicit adaptation)

Caching & Buffering: SVC-based prefix caching using HTTP-based CDN infrastructure

Buffering during sliding window creates multicast tree

Information-centric buffering in multisource scenario

Michael Grafl Scalable Video Coding in Content-Aware Networks 12

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STEP-BY-STEP WALKTHROUGH

Michael Grafl Scalable Video Coding in Content-Aware Networks 13

HB

HB

HB

CAN MANE MANE

SVC encoding

1st SVC Adaptation at MANE

2nd SVC Adaptation at MANE

SVC to AVC transcoding

SVC to AVC transcoding

Source

AVC decoding AVC

decoding

1

2 3 4

5 7

6

8

9

Source Stream

Base Layer (AVC)

Enhancement Layer 1

Enhancement Layer 2

HB

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CONCLUSIONS Towards ICN: Scalable media coding formats (e.g.,

SVC) in combination with in-network adaptation Routing & Forwarding

Caching & Buffering

QoS/QoE

Enabling content-awareness within the (core) network

Context-awareness at receiver & sender (& ICN node)

ALICANTE Towards deployment of a networked "Media Ecosystem"

Collaboration of CAN layer and Home-Box layer

Michael Grafl Scalable Video Coding in Content-Aware Networks 14

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LITERATURE [1] J. Pan, S. Paul, R. Jain, “A survey of the research on future internet

architectures”, IEEE Communications Magazine, vol.49, no.7, pp.26-36, July 2011.

[2] V. Jacobson, D. Smetters, J. Thornton, M. Plass, N. Briggs, R. Braynard, “Networking named content”, Proc. of ACM CoNEXT 2009, Rome, Italy, December 2009.

[3] H. Koumaras et al., “Media Ecosystems: A Novel Approach for Content-Awareness in Future Networks,” Future Internet: Achievements and Promising Technology, Springer Verlag, pp. 369-380, May 2011.

[4] ALICANTE Web site, http://ict-alicante.eu/.

[5] M. Wien et al., “Performance Analysis of SVC,” Circuits and Systems for Video Technology, IEEE Transactions on, vol. 17, no. 9, pp. 1194-1203, 2007.

[6] T. Stockhammer, “Dynamic adaptive streaming over HTTP – standards and design principles,” in Proceedings of the Second Annual ACM Conference on Multimedia Systems, New York, NY, USA, pp. 133–144, February 2011.

[7] M. Grafl, et al., “Scalable Video Coding in Content-Aware Networks: Research Challenges and Open Issues,” in: N. Blefari-Melazzi, G. Bianchi, and L. Salgarelli (eds.), Trustworthy Internet, Springer, pp. 349-358, June 2011.

Michael Grafl Scalable Video Coding in Content-Aware Networks 15

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THANK YOU

FOR YOUR ATTENTION!

Questions?

Michael Grafl Scalable Video Coding in Content-Aware Networks 16


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