Quality of Service in Peer-to-
Peer Media Streaming

    Darshan Purandare
    University of Central Florida
    Orlando, ...
Outline
   Peer-to-Peer (P2P) Media Streaming
   Related Work
   Current Issues
   Our Proposed Methodology
   Allian...
Introduction
   Advent of multimedia technology and broadband surge
    lead to:
       Excessive usage of P2P applicati...
Introduction Contd.

   P2P media streaming is non trivial:
       Need to playback the media in real time
           Q...
P2P Media Streaming
   Media streaming extremely expensive
       1 hour of video encoded at 300Kbps = 128.7 MB
       ...
P2P Sharing
 Content Distribution Tool
                                                  …
                  1
          ...
Major Approaches

   Major approaches
       Content Distribution Networks like Akamai
           Expensive  Only larg...
Content Distribution Networks (CDNs)
   CDN nodes deployed in multiple locations, often over
    multiple backbones
   T...
Media Streaming




                 Application Layer                      Peer-to-Peer
                    Multicast


 ...
Application Layer Multicast (ALM)

   Very sparse deployment of IP Multicast due to technical
    and administrative reas...
ALM Methodologies
   Tree Based
       Content flows from server to nodes in a tree like fashion, every node
        for...
Tree Based ALM
Mesh Based ALM
Peer-to-Peer Streaming Models
   Design flaws in ALM lead to current day P2P Streaming models based
    on chunk driven t...
CoolStreaming

   Files is chopped by server and disseminated in the swarm
   Node upon arrival obtain a peerlist of 40 ...
P2P Based Streaming Model
                                                …
                1
                            ...
Metrics
   Quality of Service
       Jitter less transmission
       Low end to end latency
   Uplink utilization
    ...
Quality of Service
   Most important metric
   Jitter: Unavailability of stream content at play time causes
    jitter
...
Uplink Utilization

   Uplink is the most sparse and important resource in
    swarm
   Summation of uplinks of all node...
Robustness and Reliability

   A Robust and Reliable P2P system should be able to
    support with an acceptable levels o...
Scalability

   Serve as many users as possible with an acceptable
    level of QoS
   Increasing number of nodes should...
Fairness

   Measured in terms of content served to the swarm
       Share Ratio = Uploaded Volume / Downloaded Volume
...
Security

   Implicitly affects other P2P Streaming metrics
   Mainly 4 types of attacks:
       Malicious garbled Payl...
Current Issues
   High buffering time
       Half a minute for popular streaming channels and around 2 minutes for
     ...
Our Proposed Methodology
   BEAM: Bit stEAMing
   Swarm based P2P model
       Uses Alliance theory for peering
      ...
POWER

        POWER




                Server


POWER                     POWER



                                  All...
Alliance Theory

   Nodes cluster in groups of 4-6 to form an alliance
   Alliance members have common trust and treaty
...
Alliance Formation
Alliance Formation
Alliance Functionality

   A node can be a member of multiple alliances
   H = Maximum number of nodes in an Alliance
 ...
Alliance Functionality
Small World Network

   Small World Network is characterized by:
       High coefficient of clustering
       Mean path...
Comparison with Random Graphs
Graph Type      Server Distance          Clustering Coefficient

Random          3.16       ...
Simulation Details
   Custom time event based simulator
   Created in Python on Linux (Ubuntu) platform
   Comparison w...
Number of Nodes vs Jitter Factor
Number of Nodes vs Latency
Number of Nodes vs % uplink utilization
Bit rate vs Jitter Factor
Bit rate vs Latency
Fairness: Num of Nodes vs Share Ratio
Node Failure vs Jitter Factor
Node Failure vs Average Latency
Number of Nodes vs Control Overhead
Results and Discussion

   BEAM has scaled well and outperformed CoolStreaming
    in almost all the metrics
   Forming ...
Conclusion

   P2P Streaming is an effective way to
    broadcast with little or no infrastructure
   BEAM has proven to...
Quality of Service in Peer-to-Peer Media Streaming
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Quality of Service in Peer-to-Peer Media Streaming

  1. 1. Quality of Service in Peer-to- Peer Media Streaming Darshan Purandare University of Central Florida Orlando, FL, USA
  2. 2. Outline  Peer-to-Peer (P2P) Media Streaming  Related Work  Current Issues  Our Proposed Methodology  Alliance Theory  Important P2P Media Streaming Metrics  Improving Locality of Traffic  Security Issues  Future Trends
  3. 3. Introduction  Advent of multimedia technology and broadband surge lead to:  Excessive usage of P2P application that includes:  Sharing of Large Videos over the internet  Video-on-Demand (VoD) applications  P2P media streaming applications  BitTorrent like P2P models suitable for bulk file transfer  P2P file sharing has no issues like QoS:  No need to playback the media in real time  Downloading takes long time, many users do it overnight
  4. 4. Introduction Contd.  P2P media streaming is non trivial:  Need to playback the media in real time  Quality of Service  Procure future media stream packets  Needs reliable neighbors and effective management  High “churn” rate – Users join and leave in between  Needs robust network topology to overcome churn  Internet dynamics and congestion in the interior of the network  Degrades QoS  Fairness policies extremely difficult to apply like tit-for-tat  High bandwidth users have no incentive to contribute
  5. 5. P2P Media Streaming  Media streaming extremely expensive  1 hour of video encoded at 300Kbps = 128.7 MB  Serving 1000 users would require 125.68 GB  Media Server cannot serve everybody in swarm  In P2P Streaming:  Peers form an overlay of nodes on top of www internet  Nodes in the overlay connected by direct paths (virtual or logical links), in reality, connected by many physical links in the underlying network  Nodes offer their uplink bandwidth while downloading and viewing the media content  Takes load off the server  Scalable
  6. 6. P2P Sharing  Content Distribution Tool … 1 … Server 3 2 … … … 5 4 … … … 1  File is chopped into pieces 3
  7. 7. Major Approaches  Major approaches  Content Distribution Networks like Akamai  Expensive  Only large infrastructure can afford  Client Server Model  Not scalable  Application Layer Multicast  Alternate to IP Multicast  Peer-to-Peer Based  Most viable and simple to use and deploy  No setup cost  Scalable
  8. 8. Content Distribution Networks (CDNs)  CDN nodes deployed in multiple locations, often over multiple backbones  These nodes cooperate with each other to satisfy an end user’s request  User request is sent to nearest CDN node, which has a cached copy  QoS improves as end user receives best possible connection  Yahoo mail uses Akamai
  9. 9. Media Streaming Application Layer Peer-to-Peer Multicast [CoolStreaming, PPLive, SO PCast,TV Ants, Feidian] Tree Based Mesh Based [NICE, ZigZag, SpreadIT] [ESM, Narada]
  10. 10. Application Layer Multicast (ALM)  Very sparse deployment of IP Multicast due to technical and administrative reasons  In ALM:  Multicasting implemented at end hosts instead of network routers  Nodes form unicast channels or tunnels between them  Overlay Construction algorithms at end hosts can be more easily applied  End hosts needs lot of bandwidth  Most ALM approaches form Tree based topology:  Simple to use  Ineffective in case of churn and node failures as incurs high recovery time
  11. 11. ALM Methodologies  Tree Based  Content flows from server to nodes in a tree like fashion, every node forwards the content to its children, which in turn forward to their children  One point of failure for a complete subtree  High recovery time  Notes Tree Base Approaches: NICE, SpreadIT, Zigzag  Mesh Based  Overcomes tree based flaws  Nodes maintain state information of many nodes  High control overhead  Notes Mesh Based approaches include Narada and ESM from CMU.
  12. 12. Tree Based ALM
  13. 13. Mesh Based ALM
  14. 14. Peer-to-Peer Streaming Models  Design flaws in ALM lead to current day P2P Streaming models based on chunk driven technology  Media content is broken down in small pieces and disseminated in the swarm  Neighboring nodes use Gossip protocol to exchange buffer information  Nodes trade unavailable pieces  Robust and Scalable  Most noted approach in recent years: CoolStreaming  PPLive, SOPCast, Fiedian, TV Ants are derivates of CoolStreaming  Proprietary and working philosophy not published  Reverse Engineered and measurement studies released
  15. 15. CoolStreaming  Files is chopped by server and disseminated in the swarm  Node upon arrival obtain a peerlist of 40 nodes from the server  Nodes contact these nodes for media content  In steady state, every node has typically 4-8 neighbors, it periodically shares it buffer content map with neighbors  Nodes exchange the unavailable content  Real world deployed and highly successful system
  16. 16. P2P Based Streaming Model … 1 … Server 3 2 … … … 5 4 … … … 1 3
  17. 17. Metrics  Quality of Service  Jitter less transmission  Low end to end latency  Uplink utilization  High uplink throughput leads to scalable P2P systems  Robustness and Reliability  Churn, Node failure or departure should not affect QoS  Scalability  Fairness  Determined in terms of content served (Share Ratio)  No user should be forced to upload much more than what it has downloaded  Security  Implicitly affects above metrics
  18. 18. Quality of Service  Most important metric  Jitter: Unavailability of stream content at play time causes jitter  Jitter less transmission ensures good media playback  Continuous supply of stream content ensures no jitters  Latency: Difference in time between playback at server and user  Lower latency keeps users interested  A live event viz. Soccer match would lose importance in crucial moments if the transmission is delayed  Reducing hop count reduces latency
  19. 19. Uplink Utilization  Uplink is the most sparse and important resource in swarm  Summation of uplinks of all nodes is the load taken off the server  Utilization = Uplink used / Uplink Available  Needs effective node organization and topology to maximize uplink utilization  High uplink throughput means more bandwidth in the swarm and hence it leads to scalable P2P systems
  20. 20. Robustness and Reliability  A Robust and Reliable P2P system should be able to support with an acceptable levels of QoS under following conditions:  High churn  Node failure  Congestion in the interior of the network  Affects QoS  Efficient peering techniques and node topology ensures robust and reliable P2P networks
  21. 21. Scalability  Serve as many users as possible with an acceptable level of QoS  Increasing number of nodes should not degrade QoS  An effective overlay node topology and high uplink throughput ensures scalable systems
  22. 22. Fairness  Measured in terms of content served to the swarm  Share Ratio = Uploaded Volume / Downloaded Volume  Randomness in swarm causes severe disparity  Many nodes upload huge volume of content  Many nodes get a free ride with no or very less contribution  Must have an incentive for an end user to contribute  P2P file sharing system like BitTorrent use tit-for-tat policy to stop free riding  Not easy to use it in Streaming as nodes procure pieces in real time and applying tit-for-tat can cause delays
  23. 23. Security  Implicitly affects other P2P Streaming metrics  Mainly 4 types of attacks:  Malicious garbled Payload insertion  Free rider – Selfish used only downloads with no uploads  Whitewasher – After being kicked out, comes again with new identity. Such nodes use IP spoofing  DDoS attack – One or more nodes collectively launch a DoS attack on media server to crack the system down  Lot of attack on P2P file sharing system but very few on Streaming  Possibility cannot be denied
  24. 24. Current Issues  High buffering time  Half a minute for popular streaming channels and around 2 minutes for less popular  Some nodes lag with their peers by more than 2 minutes in playback time.  Better Peering Strategy needed  Uneven distribution of uplink bandwidths (Unfairness)  Huge volumes of cross ISP traffic  ISPs use bandwidth throttling to limit bandwidth usage  Degrade QoS perceived at used end  Sub Optimal uplink utilization
  25. 25. Our Proposed Methodology  BEAM: Bit stEAMing  Swarm based P2P model  Uses Alliance theory for peering  Nodes cluster in small groups of 4-6 to form an alliance  High contributing nodes (Power Nodes) have high ranking based on their share ratios  Such nodes may be served directly by server  Serves as an incentive mechanism for nodes to contribute  Network topology in our model is a small world network  In small world networks, every node is connected to every other node in the swarm by a small number of path length
  26. 26. POWER POWER Server POWER POWER Alliance 1 Alliance 2 Alliance 3 Alliance 4
  27. 27. Alliance Theory  Nodes cluster in groups of 4-6 to form an alliance  Alliance members have common trust and treaty  As a node receives new content, it forwards among its alliance members first  Alliance members are mutually trusted  All members of an alliance have an active connection with other members  Applying security policies in alliance is much easier
  28. 28. Alliance Formation
  29. 29. Alliance Formation
  30. 30. Alliance Functionality  A node can be a member of multiple alliances  H = Maximum number of nodes in an Alliance  K = Maximum number of alliances a node can join  As a node procures a new stream packet from other source:  It spreads it in its alliances  Forwards different pieces to different nodes  Nodes in turn exchange pieces  Makes it mandatory for a node to upload the content  As new nodes procure content, they forward it in their other alliances  H and K impose restrictions on alliance and stop them from growing too large
  31. 31. Alliance Functionality
  32. 32. Small World Network  Small World Network is characterized by:  High coefficient of clustering  Mean path lengths comparable to mean path lengths in random graphs  Every node can be reached from any other node in a small number of hop counters (nearly logN path length)  BEAM generate node topology like a small world network  Alliance mandates a high clustering coefficient  A node has multiple alliances, i.e. it creates links with far located nodes  Mean path length is near Random graphs
  33. 33. Comparison with Random Graphs Graph Type Server Distance Clustering Coefficient Random 3.16 0.013 BEAM 3.19 0.42 •Total Node = 512 •Node Degree = 8 •High clustering coefficient signifies node connectivity in the vicinity
  34. 34. Simulation Details  Custom time event based simulator  Created in Python on Linux (Ubuntu) platform  Comparison with CoolStreaming  Chunk Driven  Most popular  Ideal for testing extreme scenarios:  Difficulty in obtaining thousands of nodes in real world implementation  Planet Lab like testbed overlay are better suites but their numbers are limited. As of Oct 2006, there are 704 machines hosted on 339 sites  Some details abstracted without loss:  Propagation Delay  TCP dynamics  Shared Bottlenecks
  35. 35. Number of Nodes vs Jitter Factor
  36. 36. Number of Nodes vs Latency
  37. 37. Number of Nodes vs % uplink utilization
  38. 38. Bit rate vs Jitter Factor
  39. 39. Bit rate vs Latency
  40. 40. Fairness: Num of Nodes vs Share Ratio
  41. 41. Node Failure vs Jitter Factor
  42. 42. Node Failure vs Average Latency
  43. 43. Number of Nodes vs Control Overhead
  44. 44. Results and Discussion  BEAM has scaled well and outperformed CoolStreaming in almost all the metrics  Forming alliance has proved to be an effective way to organize the peers  Control overhead is minimal for most combinations of H,K values  QoS is near optimal even in such random swarm environment  BEAM is robust and reliable and delivers excellent performance even under severe churn and node failures
  45. 45. Conclusion  P2P Streaming is an effective way to broadcast with little or no infrastructure  BEAM has proven to be an effective model for P2P media streaming  Alliance theory is a sound peering technique and provides robustness to the system  Security issues needs to be dealt with for DoS attacks
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