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Know thy neighbor

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Know thy neighbor's neighbor: Better Routing for Skip-Graphs and Small Worlds ... Naturally generalizes to q long range links. 6. Small Worlds. d-dimensional grid ... – PowerPoint PPT presentation

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Title: Know thy neighbor


1
Know thy neighbors neighbor Better Routing for
Skip-Graphs and Small Worlds
Moni Nao, Udi Wieder
  • ??a?as?p????? ?????s??
  • ?aµ??? ?aµp????
  • F?t??d?? ???ate????

2
Introduction
  • Aim Propose an approach for routing in DTHs
    which is better than greedy routing
  • Greedy routing move to the node that minimizes
    the L1 distance to the target.
  • ExamplesChord, Skip Nets, Skip Graphs,

3
Greedy Routing Advantages
  • Simplicity
  • Easy to understand and implement
  • Fault Tolerance
  • as long as each node has some edge towards the
    target, it is guaranteed that the message will
    reach its destination
  • Locality in the key space
  • Message do not wander in the key space

4
Greedy Routing
  • Why use something else?
  • Not degree optimal
  • Greedy -gt O(logn) ! Optimal -gt O(logn/loglogn)
  • NoN Greedy algorithm (Neighbor-of-Neighbor)
  • Enjoys the advantages of greedy, while
    being degree optimal

5
Kleinbergs model 2000
  • People ?? points on a two dimensional grid
  • Grid edges (short range)
  • One long range contact chosen with the Harmonic
    distribution
  • probability of (u,v) proportional to 1/d(u,v)2
  • Degree of each node T(logn)
  • Naturally generalizes to q long range links

6
Small Worlds
  • d-dimensional grid
  • Each edge (u,v) is connected with probality
    u-v-d
  • Degree of each node T(logn)
  • Originates from long range percolation model
  • Shares structural properties with some popular
    randomized P2P networks R-Chord, R-Hypercube,
    Skip Lists

7
The NoN-Greedy Algorithm
8
The NoN-Greedy Algorithm
  • Step (2) is implemented by putting all z in a
    search tree. Search time O(log(k2))
  • Klogn gt Search time O(loglogn)

9
Greedy vs NoN-Greedy
  • 224 nodes
  • 150 executions for each size
  • 34 improvement

10
The NoN-Greedy Algorithm
  • Phase1 the message is sent to a neighbor whose
    neighbor is close to the target
  • Phase2-greedy step the message moves to the
    neighbor of the neighbor

11
Fault Tolerance Optimistic Scenario
  • A node knows if its lists are updated
  • If not updated performs a greedy step
  • P(NoN) ½
  • P(Greedy) ½

12
Fault Tolerance Pessimistic Scenario
  • Node is unaware that its list are up-to-date
  • With probability ½ the edge (w,z) no longer
    exists
  • i) w performs a greedy step
  • ii) w performs a NoN step

13
NoN - Chord
  • Make Chord resemble the Small World
  • Each node x is connected to logn nodes y0,y1,y2
  • yi is a random point in x2i, x2i1
  • Path length O(logn/loglogn)
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