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SocialSwarm: Exploiting Distance in Social Networks for Collaborative Flash File Distribution. Presented by: Su Yingbin. Outline. Introduction SocialSwam Design Notations Algorithms Evaluation Conclusion. Tit-for-tat as incentive to upload. Want to encourage all peers to contribute

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SocialSwarm: Exploiting Distance in Social Networks for Collaborative Flash File Distribution


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socialswarm exploiting distance in social networks for collaborative flash file distribution

SocialSwarm: Exploiting Distance in Social Networks for Collaborative Flash File Distribution

Presented by: Su Yingbin

outline
Outline
  • Introduction
  • SocialSwam Design
  • Notations
  • Algorithms
  • Evaluation
  • Conclusion
tit for tat as incentive to upload
Tit-for-tat as incentive to upload
  • Want to encourage all peers to contribute
  • Peer A said to choke peer B if it (A) decides not to upload to B
  • Each peer (say A) unchokes at most 4 interested peers at any time
    • The three with the largest upload rates to A
      • Where the tit-for-tat comes in
    • Another randomly chosen (Optimistic Unchoke)
      • To periodically look for better choices
typical bittorrent incentives create inefficiencies
Typical BitTorrent incentives create inefficiencies
  • Clients typically avoid increasing the number of unchoke slots
  • Bandwidth reserved to peers won’t actually be used totally.
  • Social hubs can’t receive the highest priority in receiving file
slide5

Karame et al. show that combining locally optimal solutions of the smaller social teams would give a globally optimal solution for the entire social network.

socialswam design goal
SocialSwam Design Goal
  • Maximize collaboration between social peers
  • Maintain game-based techniques to encourage the cooperation of non-social peers
socialswarm interaction overview
SocialSwarm Interaction Overview

Retrieve social peers and non-social peers from tracker

Identifies Bob’s social peers

Coordinates chunk collection with them

Altruistically shares bandwidth with them

Interact with each other as well as standard BitTorrent clients

slide9
How ?
  • How to identify social peers and non-social peers ?
    • Social Distance
  • How to collaborate with each other among a social group as well as non-social peers ?
    • Adaptive Bandwidth Allocation
    • Chunk Prioritization
    • Optimistic Unchoke Candidate Selection
altruism between direct social peers
Altruism Between Direct Social Peers
  • I(a, b) is the number of reciprocal interactions a has had within a given time window with b
  • I(a, all) is the number of reciprocal interactions a has had with all of its peers during
  • the same window of time.
  • A(a, b) represents the proportional willingness that a peer a has to share resources with each of its direct peers
approximating socialdistance between indirect peers
Approximating SocialDistance Between Indirect Peers

-------- direct peers

Peers beyond this value are considered as non-social

the gather and share technique
The “gather-and-share” Technique
  • From the social group perspective
    • When the average social rarity for all chunks is high, allocate more bandwidth for non-social peers.
    • As the average social rarity for all chunks decreasing, allocate more bandwidth for social peers.
  • Average social rarity for all chunks:
  • Maximum percentage of bandwidth allocated to social peers:
the gather and share technique1
The “gather-and-share” Technique
  • From the social individual perspective
    • Chunk prioritization
    • Optimistic Unchoke Candidate Selection

combines the social, non-social, and overall rarities to form a combined weighted rarity for each given chunk

target a peer with the largest group of rare chunks at each time interval ti

social network data set
Social Network Data Set
  • 500 nodes with their interactions – Wall Postings – extracted from Facebook
  • Each pair of reciprocal postings is considered a single interaction.
  • Interactions are used to determine the direct level of altruism between Facebook users.
  • Beyond MaxSocialDistance are considered as non-social peers
conclusion
Conclusion
  • Typical incentives create inefficiencies
  • SocialSwarm exploits SocialDistance to reduce this inefficiencies
  • The “gather-and-share” technique achieve better performance