1. Peer-to-Peer Systems CNT 5517-5564
Dr. Sumi Helal & Dr. Choonhwa Lee
Computer & Information Science & Engineering Department
University of Florida, Gainesville, FL 32611
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2. 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

3. Outline 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

4. P2P Is More Than File Download
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

5. 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

6. Internet Video Streaming
Large-scale video broadcast over Internet
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

7. Video Streaming Approaches
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

8. IP Multicast 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

9. IP Multicast Per-group state in routers Slow deployment
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

10. Content Distribution Networks (CDNs)
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

11. DNS query for www.cdn.com
CDN Example
HTTP request for
origin server 1
DNS query for 2
client
CDN’s authoritative
DNS server 3
HTTP request for
CDN server near client
Origin server (
distributes HTML
replaces:
with
CDN company (cdn.com)
distributes gif files
uses its authoritative DNS server to route redirect requests

12. Application Layer Multicast (ALM)
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 underlying network
Most ALM approaches form tree-based topology
Tree construction & maintenance
Disruption in the event of churn and node failures

13. ALM - Pros Easy to deploy Programmable end hosts
No change to network infrastructure
Programmable end hosts
Overlay construction algorithms at end hosts can be easily applied
Application-specific customizations

14. P2P Swarming Protocol Data-driven/swarming protocol BitTorrent
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
CoolStreaming
PPLive, SopCast, Fiedian, and TVAnts are derivates of CoolStreaming
Proprietary and working philosophy not published
Reverse engineered and measurement studies released

15. P2P Swarming Protocol Pull-based/mesh-based Robustness and simplicity
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) 15

16. Tree-Push vs. Mesh-Pull

17. Tree-Push vs. Mesh-Pull
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

18. 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

19. BT-Based P2P Streaming BitTorrent Meta data (.torrent file)
Download policy (piece selection: rarest first)
Upload policy (peer selection: Tit-for-tat)

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

21. BiToS: BitTorrent Streaming
BitTorrent adapted for video streaming
Changes to BitTorrent’s piece selection algorithm

22. 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

23. CoolStreaming Membership Manager Partnership Manager Scheduler
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

24. Diagram of CoolStreaming System

25. GridMedia
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

26. Pure Random Pull-Based Protocol
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

27. Hybrid Pull-Push Protocol
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 27

28. Pull-Push Streaming Mechanism
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

29. Pull-Push Streaming Mechanism
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

30. PPLive 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

31. Mobile P2P Streaming Mobile video streaming Mobile environment
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

32. Mobile P2P Streaming Mobile node issues Other mobility considerations
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

33. Pioneering Approaches
Video proxy located at the edge of networks
Adaptive video transcoding considering the network conditions and constraints of mobile users
Distributed transcoding by fixed nodes
Sub-streams from multiple parents are assembled
Resilient to peer churns

34. 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

35. Questions?