Multi-Trust-Incentives: Difference between revisions
| Line 18: | Line 18: | ||
====Two-Step-Matrix==== |
====Two-Step-Matrix==== |
||
{| style="float:right; background:transparent; padding:0px; margin:0px;" |
|||
|[[Image:M_Quadrat.jpg|thumb|center|200px]] |
|||
|} |
|||
A two-step-matrix <math>M^2</math> describes the relation in 3 levels. |
A two-step-matrix <math>M^2</math> describes the relation in 3 levels. |
||
Revision as of 20:34, 31 July 2007
Multi-Trust-Incentives
The major problem of private history based incentive systems like Tit-for-Tat is their coverage. Resolving it requires leveraging other reputable peers’ history which leads directly to the EigenTrust mechanism. Multi-Trust-Incentives try to mix both mechanisms.
Design of Multi-Trust-Incentives
Mathematical View
One-Step-Matrix
| The Evaluation of Trust between peers is measured in a Matrix M. This N * N matrix defines a one-step rank among peers.
All values are measured as the normalized download volume that a peer i has received from a peer j during a period of time. |
Two-Step-Matrix
A two-step-matrix describes the relation in 3 levels.
Implementation
Idea
For a duration of t, a peer i computes his own matrix by normalizing all the downloads it received from a peer j. Periodically i will ask j for j's immediate friends so j computes its own matrix. This process is repeated iteratively until i can not get any more matrices from j.
Data Costs within the Maze
Within the Maze Network a peer i has about 36 friends for one day in average. Gathering Information about one-level friends needs 32KB data space in total. Even with level two, it becomes about 1MB for information about peers. Furthermore a daily update does not produce any significant overhead. But moving to higher levels costs for peer information are progressively growing. In the end this Multi-Trust Incentive was developed just for level two because it already covers more than 60% of total traffic.