presented by: su yingbin. outline introduction socialswam design notations algorithms evaluation...
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SocialSwarm: Exploiting Distance in Social Networks for Collaborative Flash
File Distribution
Presented by: Su Yingbin
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Outline
Introduction
SocialSwam Design
Notations
Algorithms
Evaluation
Conclusion
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Tit-for-tat as incentive to uploadWant to encourage all peers to contributePeer A said to choke peer B if it (A)
decides not to upload to BEach peer (say A) unchokes at most 4
interested peers at any timeThe three with the largest upload rates to A
Where the tit-for-tat comes inAnother randomly chosen (Optimistic Unchoke)
To periodically look for better choices
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Typical BitTorrent incentives create inefficienciesClients typically avoid increasing the number
of unchoke slotsBandwidth reserved to peers won’t actually
be used totally.Social hubs can’t receive the highest priority
in receiving file
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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.
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Just work as a team!
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SocialSwam Design Goal
Maximize collaboration between social peers
Maintain game-based techniques to encourage the cooperation of non-social peers
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SocialSwarm Interaction Overview1. Retrieve social peers
and non-social peers from tracker
2. Identifies Bob’s social peers
3. Coordinates chunk collection with them
4. Altruistically shares bandwidth with them
5. Interact with each other as well as standard BitTorrent clients
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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 AllocationChunk PrioritizationOptimistic Unchoke Candidate Selection
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Notations
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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 duringthe 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
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Approximating SocialDistance Between Indirect Peers
-------- direct peers
Peers beyond this value are
considered as non-social
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Notations
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Overall Rarity for Each Given Chunk
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Social Rarity for Each Given Chunk
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Non-social Rarity for Each Given Chunk
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The “gather-and-share” TechniqueFrom 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:
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The “gather-and-share” TechniqueFrom 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
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SocialSwarm in a Nutshell
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Social Network Data Set500 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
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Baseline Test Parameters
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Comparison of Basic Download Time
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Client Download Rate Comparison
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Chunk Rarity Reduction Comparison
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Effect of File Size on Peer Throughput
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Effect of Maximum SocialDistance on Peer Throughput
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Effect of Additional Seed Capacity
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Bandwidth Contribution and Unchoke Slot Allocation
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ConclusionTypical incentives create inefficiencies
SocialSwarm exploits SocialDistance to reduce this inefficiencies
The “gather-and-share” technique achieve better performance