Optimisation des DHT à partir des propriétés physiques, logiques et

sociologiques des clients

Pierre Fraigniaud CNRS

LRI, Univ. Paris-Sudhttp://www.lri.fr/~pierre

Plan

• Distributed Hash Table (DHT)• Structural properties• Sociological properties• Conclusion

Principles of DHTs

DHT • File, data, etc name• Typically: name space = [0,1[• h(file_name) = 0.10110001101

• User name • User name [0,1[• h(my_IP@) = 0.0011010110

Correspondence

01Users = { }

user x Data stored by x

Overlay network

01

x

y

zx knows the IP@ of y and z

Lookup

01

x

h(Andrei Rublev)

Node insertion

01Entry point

Examples

• CAN (D-dimensional meshes)• Chord (hypercube)• Viceroy (butterfly)• D2B, Koorde (de Bruijn)• …

Structural Properties

Desirable properties

• Small number of hops for lookup:i.e., small diameter and efficient

routing• Quick updates: i.e., small degree• Small congestion: i.e., small probability of contention

From the network point of view

Taking the inter-node distance in Internet into account!

It does not mean that closely related nodes must be close in the Overlay.

stretch = maxall routeslength(Internet route)

length(overlay route)

Solution

Theorem (Abraham & Malkhi)Under some conditions on the

physical network,……there exists an overlay network

with strech 1+ε, degree and diameter O(log n).

From the user point of view

Taking the user interests into account!

Closely related users aim at being close in the Overlay.

How to measure proximity between users?

Requests types

• Typo: h(André Roublef) vs. h(Andrei Rublev) • Structure:

Prefix search, interval, etc• Data-base type requests

Sociological Properties

Connect users sharing common interets

• Gnutella enhanced with additional links…

• Every user keeps links only with users sharing common interest (cf. Maay)

Structure of user connections

• Scale-free structure: Degree distribution = power law

Prob( deg(x)=k ) ≈ k-a

• Guided walk in scale-free graphs• Random walk• Shortest path• Neighbor with largest degree first

Rumors and legendsPath length

Network size

Random walk

Shortest path

Neighbor withhighest degree first

Using small world properties

• Milgram’s experiment six degrees of separation between indivitual

• Kleinberg’s augmented meshes capture this phenomenon

• DHT Symphony (!)• Why not just doing greedy routing?

Conclusion

Conclusion: users sociological properties seem to have more impact on DHT’s than network structural properties

Unfortunately sociological properties are difficult to model and to measure

Warning: this conclusion might be not true in other contexts, e.g., ad hoc, global computing, etc.