  Given some of the recent advances in Distributed Hash Table (DHT) based
Peer-To-Peer (P2P) systems we ask the following questions: Are there
applications where unstructured queries are still necessary (i.e., the
underlying queries do not efficiently map onto any structured framework), and
are there unstructured P2P systems that can deliver the high bandwidth and
computing performance necessary to support such applications. Toward this end,
we consider an image search application which supports queries based on image
similarity metrics, such as color histogram intersection, and discuss why in
this setting, standard DHT approaches are not directly applicable. We then
study the feasibility of implementing such an image search system on two
different unstructured P2P systems: power-law topology with percolation search,
and an optimized super-node topology using structured broadcasts. We examine
the average and maximum values for node bandwidth, storage and processing
requirements in the percolation and super-node models, and show that current
high-end computers and high-speed links have sufficient resources to enable
deployments of large-scale complex image search systems.
