CS 414 - Spring 2011 CS 414 – Multimedia Systems Design Lecture 37 – P2P Streaming and P2P...

CS 414 - Spring 2011

CS 414 – Multimedia Systems Design Lecture 37 – P2P Streaming and P2P Applications/PPLive

Klara Nahrstedt

Spring 2011

Administrative MP3 preview is on April 27

Sign-up sheet for APRIL 27 demonstration will be provided in class on April 27

Preview demonstrations on April 27, 7-9pm in 216 SC


Administration Final MP3 delivery on April 29

Demonstration time slots on April 29 will be allocated on Thursday, April 28 (TA will email to each group)

Two demonstration intervals students not in Google competition – demos 2-4pm in 216 SC, students in Google competition – demos 5-7pm in 216 SC

Pizza and Google Prizes Announcement at 7:15pm, April 29 (room 3403 SC)

Homework 2 will be out on Wednesday, April 27 Deadline, May 4, 11:59pm – submission via

compass


Outline

P2P StreamingSingle tree (previous lecture)Multiple treesMesh-based streaming

Case study: PPLive


Why P2P?

Every node is both a server and clientEasier to deploy applications at endpointsNo need to build and maintain expensive

infrastructurePotential for both performance improvement

and additional robustnessAdditional clients create additional servers for

scalability


Multiple Trees

Challenge: a peer must be internal node in only one tree, leaf in the rest


1 2

2 3 1 3

3

1 2

Source Are nodes 1, 2, 3 receiving the same data multiple times?

Multiple Description Coding (MDC)

Each description can be independently decoded (only one needed to reproduce audio/video)More descriptions received result in higher

qualityCS 414 - Spring 2011

coder

Frames 30 20 10

Packets for description 0

Packets for description n

…

3n 2n 1n

Streaming in multiple-trees using MDC Assume odd-bit/even-bit encoding --

description 0 derived from frame’s odd-bits, description 1 derived from frame’s even-bits


4

1

2 3

3

1 2

3020

10

3121

11(using RTP/UDP)

Multiple-Tree Issues

Complex procedure to locate a potential-parent peer with spare out-degreeDegraded quality until a parent found in every

tree Static mapping in trees, instead of choosing

parents based on their (and my) bandwidthAn internal node can be a bottleneck


Mesh-based streaming Basic idea

Report to peers the packets that you haveAsk peers for the packets that you are

missingAdjust connections depending on in/out

bandwidth


Description 0/1/2

Description 1

Description 0

Description 1,2

Description 0,1,2

(Nodes are randomly connected to their peers, instead of statically)

Description 0/1/2

(mesh uses MDC)

Content delivery


1

4

10 11 12

5

2

6

13 14 15

7

3

8

16 17

9

Description 0 Description 2Description 1

(1) Diffusion Phase ( ) (2) Swarming Phase ( )

(Levels determined by hops to source)

Diffusion Phase

As a new segment (set of packets) of length L becomes available at source every L seconds Level 1 nodes pull data units

from source, then level 2 pulls from level 1, etc.

Recall that reporting and pulling are performed periodically


30 20 10

…

32 22 12

40

42

Segment 0Segment 1

…

…

Have segment 0

3

Send meSegment 0

22

12

(during period 0)

3 Have segment 0

9

22

12

(during period 1)

Send meSegment 0

(drawings follow previous example)

Swarming Phase

At the end of the diffusion all nodes have at least one data unit of the segment

Pull missing data units from (swarm-parent) peers located at same or lower level

Can node 9 pull new data units from node 16? Node 9 cannot pull data in a single swarm interval

CS 414 - Spring 2011(drawings follow previous example)

10 11 12

2

13 14 15

7

16 17

9

20

10

2111

21 11

1121

1020

Purdue

Stan1

Stan2

Berk2

Overlay Tree

Stanford

Berkeley

Dumb Network

Gatech

Gatech

Berk1

Stan1

Stan2

Berk1

Berk2

Source:

Purdue

Single Tree/Multi-tree/Mesh use Overlay P2P Multicast

Source: Sanjay Rao’s lecture from PurdueCS 414 - Spring 2011

Overlay Performance

Even a well-designed overlay cannot be as efficient as IP Mulitcast But performance penalty can be kept low Trade-off some performance for other benefits

Increased Delay

Dumb Network

GatechDuplicate Packets:

Bandwidth Wastage

Stanford

Berkeley

Source: Sanjay Rao’s lecture from PurdueCS 414 - Spring 2011

Traffic Distribution (2006) and New Trends (P4P)


P4P – ISPs and P2P TrafficWork together

Source: http://www.openp4p.net/

P2P Applications

Many P2P applications since the 1990sFile sharing

Napster, Gnutella, KaZaa, BitTorrent

Internet telephony Skype

Internet television PPLive, CoolStreaming


PPLive Current Viewers during Olympics 2008


Case Study: PPLive

Very popular P2P IPTV applicationFrom Huazhong U. of Science and

Technology, ChinaFree for viewersOver 100,000 simultaneous viewers and

400,00 viewers dailyOver 200+ channelsWindows Media Video and Real Video format


PPLive Overview


PPLive Design Characteristics Gossip-based protocols

Peer management Channel discovery TCP used for signaling

Data-driven p2p streaming TCP used for video streaming Peer client contacts multiple active peers to download media content of the

channel Cached contents can be uploaded from a client peer to other peers watching

the same channel Received video chunks are reassembled in order and buffered in queue of

PPLive TV Engine (local streaming)


PPLive Architecture

1. Contact channel server for available channels

2. Retrieve list of peers watching selected channel

3. Find active peers on channel to share video chunks Source: “Insights into PPLive: A Measurement

Study of a Large-Scale P2P IPTV System” by Hei et al.


P2P Streaming Process


TV Engine – responsible for • downloading video chunks from PPLive network• streaming downloaded video to local media player

Download and Upload Video Rate over Time at CCTV3 Campus


Evolution of active video peer connections on CCTV3 Network


PPLive Channel Size Analysis


Conclusion Couple of Lessons Learned

Structure of PPLive overlay is close to random PPLive peers slightly peer to have closer neighbors and

peers can attend simultaneous overlays Improves streaming quality

Geometrically distributed session lenghts of nodes can be used to accurately model node arrival and departure

Major differences between PPLive overlays and P2P file-sharing overlays!!!


Background Large-scale video broadcast over Internet (Internet TV such

as PPLIve, YouTube) Real-time video streaming Need to support large numbers of viewers

AOL Live 8 broadcast peaked at 175,000 (July 2005) CBS NCAA broadcast peaked at 268,000 (March 2006) NBC Olympic Games in 2008 served total 75.5 million streams BBC served almost 40 million streams of Olympic Games 2008

(http://newteevee.com/2008/08/28/final-tally-olympics-web-and-p2p-numbers/)

Very high data rate TV quality video encoded with MPEG-4 would require 1.5 Tbps aggregate

capacity for 100 million viewers NFL Superbowl 2007 had 93 million viewers in the U.S. (Nielsen Media

Research)


Reading “Opportunities and Challenges of Peer-to-Peer Internet Video

Broadcast” by Liu et al. “Insights into PPLive: A Measurement Study of a Large-Scale

P2P IPTV System” by Hei et al. “Mapping the PPLive Network: Studying the Impacts of Media

Streaming on P2P Overlays” by Vu et al. Some lecture material borrowed from the following sources

Sanjay Rao’s lecture on P2P multicast in his ECE 695B course at Purdue “Insights into PPLive: A Measurement Study of a Large-Scale P2P IPTV

System” by Hei et al. “Mapping the PPLive Network: Studying the Impacts of Media Streaming

on P2P Overlays” by Vu et al.


CS 414 - Spring 2011 CS 414 – Multimedia Systems Design Lecture 37 – P2P Streaming and P2P...

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