A least resistance path to the analysis of unstructured overlay networks
Rapport, 2008
Unstructured overlay networks for peer-to-peer applications combined with stochastic algorithms
for interest-based clustering and resource location are attractive due to low-maintenance
costs and inherent fault-tolerance properties. Moreover, there is a relatively large volume of experimental
evidence that these methods are efficiency-wise a good alternative to structured methods,
which require more sophisticated algorithms for maintenance and fault-tolerance. Specifically in
the case of interest-based clustering, it has been recently suggested that a resource location strategy
based on non-trivial randomwalks can be used to construct an overlay network with scale-free
and clustering properties, which can be navigated efficiently. However, currently there is a very
limited selection of appropriate tools to use in evaluating performance and other properties of
such non-trivial methods.
We present a framework for analyzing unstructured overlays and stochastic algorithms on
them, connecting the corresponding graphs, random walks and resistor networks by using elementary
linear algebra calculations. We express the framework in a way that can be used in
various contexts regarding the overlay network and statistical methods. Furthermore, we demonstrate
its usage by studying non-trivial random walks in overlays with power-law node degree
distribution; in particular we address a broad set of topics of interest for peer-to-peer overlays,
including content-replication efficiency, fault-tolerance, query-replication efficiency and resource
constraint handling.
peer-to-peer networks
random walks