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Peer-to-Peer Systems CNT 5517-5564 Dr. Sumi Helal & Dr. Choonhwa Lee Computer & Information Science & Engineering Department University of Florida, Gainesville, FL 32611 {helal, chl}@cise.ufl.edu
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Dr. Sumi Helal & Dr. Choonhwa Lee Computer & Information Science & Engineering Department University of Florida, Gainesville, FL 32611 {helal, chl}@cise.ufl.edu.

Mar 31, 2015

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Page 1: Dr. Sumi Helal & Dr. Choonhwa Lee Computer & Information Science & Engineering Department University of Florida, Gainesville, FL 32611 {helal, chl}@cise.ufl.edu.

Peer-to-Peer Systems CNT 5517-5564

Dr. Sumi Helal & Dr. Choonhwa LeeComputer & Information Science & Engineering Depart-

mentUniversity of Florida, Gainesville, FL 32611

{helal, chl}@cise.ufl.edu

Page 2: Dr. Sumi Helal & Dr. Choonhwa Lee Computer & Information Science & Engineering Department University of Florida, Gainesville, FL 32611 {helal, chl}@cise.ufl.edu.

The State of the Art of P2P Video Streaming

Slide courtesy: Prof. Darshan Purandare at University of Central Florida, USA Dr. Meng ZHANG, Dyyno Inc., USA Jan David Mol, Delft University of Technology, The Netherlands

Page 3: Dr. Sumi Helal & Dr. Choonhwa Lee Computer & Information Science & Engineering Department University of Florida, Gainesville, FL 32611 {helal, chl}@cise.ufl.edu.

Introduction Video Streaming Approaches

◦ IP Multicast◦ Content Distribution Network◦ Application Layer Multicast◦ Peer-to-Peer Swarming Protocol

Noteworthy P2P Streaming Systems◦ BT-Based Protocols◦ CoolStreaming, GridMedia, PPLive

Mobile P2P Streaming

Outline

Page 4: Dr. Sumi Helal & Dr. Choonhwa Lee Computer & Information Science & Engineering Department University of Florida, Gainesville, FL 32611 {helal, chl}@cise.ufl.edu.

P2P Protocols: 1999: Napster, End System Multicast (ESM) 2000: Gnutella, eDonkey 2001: Kazaa 2002: eMule, BitTorrent 2003: Skype 2004: Coolstreaming, GridMedia, PPLive 2005~: TVKoo, TVAnts, PPStream, SopCast, …

Next: VoD, IPTV, Gaming

P2P Is More Than File Down-load

Page 5: Dr. Sumi Helal & Dr. Choonhwa Lee Computer & Information Science & Engineering Department University of Florida, Gainesville, FL 32611 {helal, chl}@cise.ufl.edu.

Internet Traffic

Internet video is ~1/4 of consumer Internet traffic – not including P2P

All forms of video ~90% by 2012 TV, VoD, Internet, and

P2P Mobile data traffic

will double every year from now though 2012

Page 6: Dr. Sumi Helal & Dr. Choonhwa Lee Computer & Information Science & Engineering Department University of Florida, Gainesville, FL 32611 {helal, chl}@cise.ufl.edu.

Large-scale video broadcast over Inter-net◦ Real-time video streaming◦ Large numbers of viewers

AOL Live 8 broadcast peaked at 175,000 (July 2005) CBS NCAA broadcast peaked at 268,000 (March

2006) NFL Superbowl 2007 had 93 million viewers in the

U.S. (Nielsen Media Research)

◦ Very high data rate TV quality video encoded with MPEG-4 would require

1.5 Tbps aggregate capacity for 100 million viewers

Internet Video Streaming

Page 7: Dr. Sumi Helal & Dr. Choonhwa Lee Computer & Information Science & Engineering Department University of Florida, Gainesville, FL 32611 {helal, chl}@cise.ufl.edu.

IP Multicast Content Distribution Networks

◦ Expensive

◦ Akamai, Limelight, etc

Application Layer Multicast◦ Alternative to IP Multicast

Peer-to-Peer Based◦ Scalable

◦ No setup cost

◦ Viable

Video Streaming Ap-proaches

Page 8: Dr. Sumi Helal & Dr. Choonhwa Lee Computer & Information Science & Engineering Department University of Florida, Gainesville, FL 32611 {helal, chl}@cise.ufl.edu.

Network layer solution Internet routers responsible

for multicasting◦ Group membership: remember

group members for each multicast session

◦ Multicast routing: route data to members

Efficient bandwidth usage◦ Network topology is best known

in network layer

IP Multicast

Page 9: Dr. Sumi Helal & Dr. Choonhwa Lee Computer & Information Science & Engineering Department University of Florida, Gainesville, FL 32611 {helal, chl}@cise.ufl.edu.

Per-group state in routers◦ High complexity, especially in core routers◦ Scalability concern◦ Violation of the end-to-end design principle: ‘stateless’

Slow deployment◦ Changes at infrastructural level◦ IP multicast is often disabled in routers

Difficult to support higher layer functionality◦ E.g., error control, flow control, and congestion control

IP Multicast

Page 10: Dr. Sumi Helal & Dr. Choonhwa Lee Computer & Information Science & Engineering Department University of Florida, Gainesville, FL 32611 {helal, chl}@cise.ufl.edu.

CDN nodes deployed at strategic locations These nodes cooperate with each other to

satisfy an end user’s request User request is forwarded to a nearest CDN

node, which has a cached copy QoS improves, as end user receives best

possible connection Akamai, Limelight, etc

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Content Distribution Networks (CDNs)

Page 11: Dr. Sumi Helal & Dr. Choonhwa Lee Computer & Information Science & Engineering Department University of Florida, Gainesville, FL 32611 {helal, chl}@cise.ufl.edu.

CDN Example

Origin server (www.foo.com) distributes HTML replaces: http://www.foo.com/sports.ruth.gif

with http://www.cdn.com/www.foo.com/sports/ruth.gif

HTTP request for

www.foo.com/sports/sports.html

DNS query for www.cdn.com

HTTP request for

www.cdn.com/www.foo.com/sports/ruth.gif

1

2

3

origin server

CDN’s authoritative DNS server

CDN server near client

client

CDN company (cdn.com) distributes gif files uses its authoritative

DNS server to route redirect requests

Page 12: Dr. Sumi Helal & Dr. Choonhwa Lee Computer & Information Science & Engineering Department University of Florida, Gainesville, FL 32611 {helal, chl}@cise.ufl.edu.

Application layer solution◦ Multicast functionality in end systems◦ End systems participate in multicast

via an overlay structure◦ Overlay consists of application-layer

links◦ Application-layer link is a logical link

consisting of one or more links in un-derlying network

Most ALM approaches form tree-based topology◦ Tree construction & maintenance◦ Disruption in the event of churn and node

failures

Application Layer Multicast (ALM)

Page 13: Dr. Sumi Helal & Dr. Choonhwa Lee Computer & Information Science & Engineering Department University of Florida, Gainesville, FL 32611 {helal, chl}@cise.ufl.edu.

Easy to deploy◦ No change to network infrastructure

Programmable end hosts◦ Overlay construction algorithms at end hosts can

be easily applied◦ Application-specific customizations

13

ALM - Pros

Page 14: Dr. Sumi Helal & Dr. Choonhwa Lee Computer & Information Science & Engineering Department University of Florida, Gainesville, FL 32611 {helal, chl}@cise.ufl.edu.

Data-driven/swarming protocol◦ Media content is broken down in

small pieces and disseminated in a swarm

◦ Neighbor nodes use a gossip protocol to exchange their buffer map

◦ Nodes trade unavailable pieces BitTorrent

P2P Swarming Protocol

CoolStreaming◦ PPLive, SopCast, Fiedian, and TVAnts are derivates of

CoolStreaming◦ Proprietary and working philosophy not published◦ Reverse engineered and measurement studies

released

Page 15: Dr. Sumi Helal & Dr. Choonhwa Lee Computer & Information Science & Engineering Department University of Florida, Gainesville, FL 32611 {helal, chl}@cise.ufl.edu.

P2P Swarming Protocol

Pull-based/mesh-based◦ Redundant chunk avoidance

Robustness and simplicity◦ Data availability information rather than an explicit

structure to guide data flow (i.e., no need for streaming tree construction)

◦ Periodical exchange of data availability with random partners and subsequent retrieval of missing data (i.e., minimal impact from upstream node failures)

Higher overhead and longer streaming delay ◦ Real-time scheduling constraints (i.e., need for good peer

and chunk selection algorithms)

Page 16: Dr. Sumi Helal & Dr. Choonhwa Lee Computer & Information Science & Engineering Department University of Florida, Gainesville, FL 32611 {helal, chl}@cise.ufl.edu.

Tree-Push vs. Mesh-Pull

Page 17: Dr. Sumi Helal & Dr. Choonhwa Lee Computer & Information Science & Engineering Department University of Florida, Gainesville, FL 32611 {helal, chl}@cise.ufl.edu.

Tree Based◦ Content flows from server to nodes along the tree◦ Node failures affect a complete sub-tree◦ Long recovery time

Mesh Based◦ Nodes maintain state information of neighbor nodes◦ Resilient to node failure◦ High control overhead

Tree-Push vs. Mesh-Pull

Page 18: Dr. Sumi Helal & Dr. Choonhwa Lee Computer & Information Science & Engineering Department University of Florida, Gainesville, FL 32611 {helal, chl}@cise.ufl.edu.

Why Is P2P Streaming Hard?

Real-time constraints• Pieces needed in a sequential order and on time

Bandwidth constraints• Download speed >= video speed

High user expectations• Users spoiled with low start-up time and no/little loss

High churn rate • Robust network topology to minimize churn impact

Fairness difficult to achieve• High bandwidth peers have no incentive to contribute

Page 19: Dr. Sumi Helal & Dr. Choonhwa Lee Computer & Information Science & Engineering Department University of Florida, Gainesville, FL 32611 {helal, chl}@cise.ufl.edu.

BT-Based P2P Streaming

BitTorrento Meta data (.torrent file)o Download policy (piece selection: rarest first)o Upload policy (peer selection: Tit-for-tat)

Page 20: Dr. Sumi Helal & Dr. Choonhwa Lee Computer & Information Science & Engineering Department University of Florida, Gainesville, FL 32611 {helal, chl}@cise.ufl.edu.

20

New Download Policy

Request highest priority pieces High prio: download in-order Mid/low prio: download rarest-first Effect:

• dl speed = video speed: peer stays in high prio• dl speed > video speed: peer is often in mid/low prio

Page 21: Dr. Sumi Helal & Dr. Choonhwa Lee Computer & Information Science & Engineering Department University of Florida, Gainesville, FL 32611 {helal, chl}@cise.ufl.edu.

BiToS: BitTorrent Streaming

BitTorrent adapted for video streaming Changes to BitTorrent’s piece selection algorithm

Page 22: Dr. Sumi Helal & Dr. Choonhwa Lee Computer & Information Science & Engineering Department University of Florida, Gainesville, FL 32611 {helal, chl}@cise.ufl.edu.

CoolStreaming Video file is chopped and disseminated in a

swarm Node upon arrival obtains a list of 40 peers from

the server Node contacts these peers to join the swarm Every node has typically 4-8 neighbors,

periodically sharing its buffer map with them Node exchanges missing chunks with its

neighbors Deployed in the Internet and highly successful

Page 23: Dr. Sumi Helal & Dr. Choonhwa Lee Computer & Information Science & Engineering Department University of Florida, Gainesville, FL 32611 {helal, chl}@cise.ufl.edu.

Membership Manager◦ Maintains a list of members in the group◦ Periodically generates membership messages◦ Distributes it using Scalable Gossip Membership Protocol

(SGAM) Partnership Manager

◦ Partners are members that have expected data segments ◦ Exchanges Buffer Map (BM) with partners◦ Buffer Map contains availability information of segments

Scheduler◦ Determines which segment should be obtained from which partner◦ Downloads segments from partners and uploads their wanted

segments

CoolStreaming

Page 24: Dr. Sumi Helal & Dr. Choonhwa Lee Computer & Information Science & Engineering Department University of Florida, Gainesville, FL 32611 {helal, chl}@cise.ufl.edu.

Diagram of CoolStreaming System

Page 25: Dr. Sumi Helal & Dr. Choonhwa Lee Computer & Information Science & Engineering Department University of Florida, Gainesville, FL 32611 {helal, chl}@cise.ufl.edu.

Designed to support large-scale live video streaming over the Internet

The first generation: Gridmedia I◦ Mesh-based multi-sender structure◦ Combined with IP multicast◦ First release: May 2004

The second generation: Gridmedia II◦ Unstructured overlay◦ Push-pull streaming mechanism◦ First release: Jan. 2005

GridMedia

Page 26: Dr. Sumi Helal & Dr. Choonhwa Lee Computer & Information Science & Engineering Department University of Florida, Gainesville, FL 32611 {helal, chl}@cise.ufl.edu.

Original GridMedia Overlay construction

◦ Peers self-organize into a richly connected random mesh

Video delivery◦ Peers periodically notifies its neighbor of what packets

they hold in the current window of interest◦ Each peer randomly chooses a neighbor to request

missing packets◦ If a packet does not arrive (i.e., timeout), it is repeatedly

requested from a randomly selected neighbor until the packet slides out of the window

Pure Random Pull-Based Proto-col

Page 27: Dr. Sumi Helal & Dr. Choonhwa Lee Computer & Information Science & Engineering Department University of Florida, Gainesville, FL 32611 {helal, chl}@cise.ufl.edu.

Hybrid Pull-Push Proto-col Pull-based protocol has trade-off between

control overhead and delay◦ To minimize the delay

Node notifies its neighbors of packet arrivals immediately

Neighbors also request the packet immediately large control overhead

◦ To decrease the overhead Node waits until a group of packets arrive before

informing its neighbors Neighbors can also request a batch of packets at a

time considerable delay

Page 28: Dr. Sumi Helal & Dr. Choonhwa Lee Computer & Information Science & Engineering Department University of Florida, Gainesville, FL 32611 {helal, chl}@cise.ufl.edu.

timePush PushPush PushPull Pull

Add new partner Add new partner

Subscribe video packets from partners at the beginning of push time interval

Node enters

Pull-Push Streaming Mecha-nism◦ Pull mechanism as startup◦ Successful pulls trigger packet pushes by the

neighbors◦ Every node subscribes to pushing packets from the

neighbors◦ Lost packets during the push interval are recovered by

pull mechanism

Page 29: Dr. Sumi Helal & Dr. Choonhwa Lee Computer & Information Science & Engineering Department University of Florida, Gainesville, FL 32611 {helal, chl}@cise.ufl.edu.

n-sub streams: packets with sequence number s % n

Loop avoidance◦ For n-sub streams, there are n packets in a packet group◦ Packet party is composed of multiple packet groups.◦ Push switching is determined by the pull results of the first

packet group in a packet party

Pull-Push Streaming Mecha-nism

Page 30: Dr. Sumi Helal & Dr. Choonhwa Lee Computer & Information Science & Engineering Department University of Florida, Gainesville, FL 32611 {helal, chl}@cise.ufl.edu.

Data-driven P2P streaming Gossip-based protocols

◦ Peer management◦ Channel discovery

Very popular P2P IPTV application◦ Over 100,000 simultaneous viewers and 40,000 viewers

daily◦ Over 200+ channels◦ Windows Media Video and Real Video format

PPLive

Page 31: Dr. Sumi Helal & Dr. Choonhwa Lee Computer & Information Science & Engineering Department University of Florida, Gainesville, FL 32611 {helal, chl}@cise.ufl.edu.

Mobile video streaming◦ Rapid growth of mobile P2P communication◦ Video streaming expected to rise to as high as

91% of the Internet traffic in 2014 Mobile environment

◦ Increase of mobile and wireless peers◦ Unsteady network connections◦ Battery power◦ Various video coding for mobile devices◦ Frequent node churn◦ Security

Mobile P2P Streaming

Page 32: Dr. Sumi Helal & Dr. Choonhwa Lee Computer & Information Science & Engineering Department University of Florida, Gainesville, FL 32611 {helal, chl}@cise.ufl.edu.

Mobile P2P Streaming

Mobile node issues◦ Uplink vs. downlink bandwidth◦ Battery power◦ Multiple interfaces◦ Geo-targeting

Other mobility considerations◦ Processing power◦ Link layer mobility◦ Mobile IP & proxy mobile IP◦ Tracker mobility

Page 33: Dr. Sumi Helal & Dr. Choonhwa Lee Computer & Information Science & Engineering Department University of Florida, Gainesville, FL 32611 {helal, chl}@cise.ufl.edu.

Pioneering Approaches Video proxy located at the edge of networks

◦ Adaptive video transcoding considering the net-work conditions and constraints of mobile users

Distributed transcoding by fixed nodes◦ Sub-streams from multiple parents are assembled◦ Resilient to peer churns

Page 34: Dr. Sumi Helal & Dr. Choonhwa Lee Computer & Information Science & Engineering Department University of Florida, Gainesville, FL 32611 {helal, chl}@cise.ufl.edu.

Pioneering Approaches Hierarchical overlay

◦ Multiple network interfaces – access link vs. sharing link

◦ Peer fetches a video thru cellular networks (WAN) to share it with others over local networks (LAN)

Cooperative video streaming◦ P2P-based application layer channel bonding in

resource-constrained mobile environments◦ Similar, in spirit, to channel/link bundling

technology at link layer to efficiently leverage the combined capacity of all access links

Page 35: Dr. Sumi Helal & Dr. Choonhwa Lee Computer & Information Science & Engineering Department University of Florida, Gainesville, FL 32611 {helal, chl}@cise.ufl.edu.

Questions?