dr. sumi helal & dr. choonhwa lee computer & information science & engineering...
TRANSCRIPT
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
10
Content Distribution Networks (CDNs)
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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
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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)
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Easy to deploy◦ No change to network infrastructure
Programmable end hosts◦ Overlay construction algorithms at end hosts can
be easily applied◦ Application-specific customizations
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ALM - Pros
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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
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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)
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Tree-Push vs. Mesh-Pull
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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
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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
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BT-Based P2P Streaming
BitTorrento Meta data (.torrent file)o Download policy (piece selection: rarest first)o Upload policy (peer selection: Tit-for-tat)
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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
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BiToS: BitTorrent Streaming
BitTorrent adapted for video streaming Changes to BitTorrent’s piece selection algorithm
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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
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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
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Diagram of CoolStreaming System
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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Questions?