Challenges, Design and Analysis of a Largescale P2PVoD System Yan Huang, Tom Z. J. Fu, DahMing Chiu,


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Challenges Design and Analysis of a Large-scale
P2P-VoD SystemYan Huang Tom Z. J. Fu Dah-Ming
Chiu John C. S. Lui and Cheng Huang

• 2008. 10. 6.
• SeungHo Lee

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Outline

• P2P overview
• An architecture of a P2P-VoD system
• Performance metrics
• Measurement results and analysis
• Future works

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P2P Overview

• Advantages of P2P
• Users help each other so that the server load is
  significantly reduced.
• P2P increases robustness in case of failures by
  replicating data over multiple peers.
• P2P services
• P2P file downloading BitTorrent and Emule
• P2P live streaming Coolstreaming and PPLive
• P2P video-on-demand (P2P-VoD) PPLive
• Like P2P streaming systems P2P-VoD systems also
  deliver the content by streaming but peers can
  watch different parts of a video at the same
  time.
• P2P-VoD systems require each user to contribute a
  small amount of storage (usually 1GB) instead of
  only the playback buffer in memory as in the P2P
  streaming systems

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Ref P2P Protocols and Applications
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P2P-VoD system

• Major components
• Peers
• Servers the source of content
• Trackers help peers connect to other peers to
  share the same content
• A bootstrap server helps peers to find a
  suitable tracker and to perform other
  bootstrapping functions
• Other servers
• log servers log significant events for data
  measurement
• transit servers help peers behind NAT boxes

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Segment sizes

• How to divide a video into multiple pieces
• Small segment size gives more flexibility to
  schedule which piece should be uploaded from
  which neighboring peer.
• The larger the segment size the smaller the
  overhead.
• Header overhead
• Bitmap overhead
• Protocol overhead
• The video player expects a certain minimum size
  for a piece of content to be viewable.
• Segmentation of a movie in PPLives VoD system

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Replication Strategy

• Goal
• To make the chunks as available to the user
  population as possible to meet users viewing
  demand while without incurring excessive
  additional overheads
• Considerations
• Whether to allow multiple movies be cached
• Multiple movie cache (MVC) / single movie cache
  (SVC)
• Whether to pre-fetch or not
• Which chunk/movie to remove when the disk cache
  is full
• Least recently used (LRU) / least frequently used
  (LFU)

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Content Discovery

• Content advertising and look-up methods
• Trackers
• Used to keep track of which peers replicate a
  given movie
• As soon as a user starts watching a movie the
  peer informs its tracker that it is replicating
  that movie.
• When a peer wants to start watching movie it
  goes to the tracker to find out which other peers
  have that movie.
• Gossip method
• Discovering where chunks are is by the gossip
  method.
• This cuts down on the reliance on the tracker
  and makes the system more robust.
• DHT
• Used to automatically assign movies to trackers
  to achieve some level of load balancing.

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Piece Selection

• Which piece to download first
• Sequential select the piece that is closest to
  what is needed for the video playback
• Rarest first selecting the rarest piece helps
  speeding up the spread of pieces hence
  indirectly helps streaming quality.
• Anchor-based when a user tries to jump to a
  particular location in the movie if the piece
  for that location is missing then the closest
  anchor point is used instead.

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Transmission Strategy

• Goals
• Maximize downloading rate
• Minimize the overheads
• Strategies (by levels of aggressiveness)
• A peer can send a request for the same content to
  multiple neighbors simultaneously
• A peer can request for different content from
  multiple neighbors simultaneously (PPLives
  choice)
• For playback rate of 500Kbps 8-20 neighbors is
  the best. More than this number can still improve
  the achieved rate but at the expense of heavy
  duplication rate.
• A peer can work with one neighbor at a time.

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Other Design Issues

• NAT and firewalls
• Discovering different types of NAT boxes
• Pacing the upload rate and request rate
• Content authentication
• Chunk level authentication
• Some pieces may be polluted and cause poor
  viewing experience locally at a peer.
• If a peer detects a chunk is bad discard it.
• Piece level authentication

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What to measure

• User behavior
• includes the user arrival patterns and how long
  they stayed watching a movie
• used to improve the design of the replication
  strategy
• External performance metrics
• includes user satisfaction and server load
• used to measure the system performance perceived
  externally
• Health of replication
• measures how well a P2P-VoD system is replicating
  a content
• used to infer how well an important component of
  the system is doing

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User Behavior

• MVR (movie viewing record)

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User Satisfaction

• Simple fluency
• measures the fraction of time a user spends
  watching a movie out of the total time he spends
  waiting for and watching that movie
• R(m i) the set of all MVRs for a given movie
  m and user i
• n(m i) the number of MVRs in R(m i)
• r one of the MVRs in R(m i)

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User Satisfaction (cont)

• User satisfaction index
• considers the quality of the delivery of the
  content
• r(Q) a grade for the average viewing quality
  for an MVR r

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Health of Replication

• Three levels
• Movie level
• The number of active peers who have advertised
  storing chunks of that movie
• The information that the tracker collects about
  movies
• Weighted movie level
• Considers the fraction of chunks a peer has in
  computing the index
• Chunk bitmap level
• The number of copies each chunk of a movie is
  stored by peers
• Various other statistics can be computed the
  average number of copies of a chunk in a movie
  the minimum number of chunks the variance of the
  number of chunks.

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Statistics on video objects

• Overall statistics of the three typical movies

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Statistics on user behavior (1)

• Interarrival time distribution of viewers

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Statistics on user behavior (2)

• View duration distribution

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Statistics on user behavior (3)

• Start position distribution

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Health index of Movies (1)

• Number of peers that own the movie

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Health index of Movies (2)

• Average owning ratios for different chunks

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Health index of Movies (3)

• Chunk availability and chunk demand

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Health index of Movies (4)

• The available to demand ratios

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User Satisfaction Index (1)

• Generating fluency index
• The computation of F(m i) is carried out by the
  client software.
• The client software reports all MVRs and the
  fluency F(m i) to the log server whenever a
  stop-watching event occurs.
• The STOP button is pressed
• Another movie/programme is selected
• The user turns off the P2P-VoD software

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User Satisfaction Index (2)

• The number of fluency records
• A good indicator of the number of viewers of the
  movie

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User Satisfaction Index (3)

• The distribution of fluency index

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Future works

• Further research in P2P-VoD systems
• How to design a highly scalable P2P-VoD system to
  support millions of simultaneous users
• How to perform dynamic movie replication
  replacement and scheduling so as reduce the
  workload at the content servers
• How to quantify various replication strategies so
  as to guarantee a high health index
• How to select proper chunk and piece transmission
  strategies so as to improve the viewing quality
• How to accurately measure and quantify the user
  satisfaction level