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P2P storage trading system

P2P storage trading system. (A preliminary idea) Presenter: Lin Wing Kai (Kai). Model. Peers join the system to perform the file replication. The files have intrinsic popularities. When a peer replicate a file, he can earn some credits. Intrinsic popularities

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P2P storage trading system

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  1. P2P storage trading system (A preliminary idea) Presenter: Lin Wing Kai (Kai)

  2. Model • Peers join the system to perform the file replication. • The files have intrinsic popularities. • When a peer replicate a file, he can earn some credits. • Intrinsic popularities • Number of peers replicating the file. • Each peer will have a fixed storage space. • The goal of each peer is to replicate the set of files so that the peer can earn the most credits.

  3. Assumptions (I) • An incentive system is possible for peers to earn credits based on replication. • Perfect information on the market. • Peers can estimate the intrinsic file popularities correctly. • Peers know each other replication decision.

  4. Terminologies (I) • N peers in the system, indexed by i. • P = {1, 2, … i, …, N} • Peer has storage space si • K files in the system, indexed by j. • F = {1, 2, … j, …, K} • Each file has intrinsic popularity lj • L = [lj], j = {1… K}, lj =[0, 1] • File replication vector Ri • Ri = [ri,j: ri,j = 1 when peer i replicate file j] • Ri is a vector of length K.

  5. Terminologies (II) • The file replication matrix M, is a NxK dimensional matrix. • Row vector is the file replication vector Ri of peer i. • Column vector Uj indicate the set of peers that replicate file j. =Ri =Uj, uj = sum(Uj)

  6. Terminologies (III) • uj is the number of peers replicate file j. • File popularity normalized function f (lj, uj) • lj = f(lj, uj) • Peers earn credits of a file equal to its normalized popularity lj.

  7. Simulation setup • 20 peers • Each peer has 10 units of storage space. • 500 files • Each file cost 1 unit of storage space. • File popularities are uniform in [0, 1] • Normalized function f() = lj/ uj • One peer makes his replication decision at each iteration.

  8. Results (A - I) • The credits gained by each peer: The credits converge

  9. Results (A - II) • The normalized files credits: These files are replicated

  10. Simple observations • An equilibrium exists in the system. • Peers earn approximate the same credits. • Equilibrium converge very fast. • At equilibrium, the files can be divided into two types: • Some files are replicated. These files have similar normalized file popularities. • Some files are not replicated.

  11. Plausible explanation • In the homogeneous peers environment, we expect all peers can earn similar credits because: • If peer i1 can find a “method” to earn more credits than i2, i2 can simply use the same method to earn more credits than i1. • For example, copy cat strategy.

  12. Simulation B • Partial information in the market. • Peers can still estimate the file intrinsic popularities. • Peers do not know other peers decision. • The credits of a file are determined by the peers. • Each peer can set the file credits a certain value. • Another peer join to the system and if he see this price, he simply set the price lower by delta.

  13. Results (B - I) • The credits gained by each peer:

  14. Extension • Perfect information is unrealistic: • Peers do not know the action by other peers. • Peers do not know the file popularities. • The file popularities are estimated from the peers demand characteristics. • How to characterize the system equilibrium in this case?

  15. Thank you • ~ END~

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