Clustering wavelets to speed-up data dissemination in structured P2P MANETs

This paper introduces a fast data dissemination method for structured peer-to-peer networks. The work is motivated on one side by the increase in non-volatile memory available on mobile devices and, on the other side, by observed behavioral patterns of the users. We envision a scenario where users come together for short periods of time (e.g. public transport, conference sessions) and wish to be able to share large collections of data. With hundreds and even thousands of data, items stored on small devices, content publication is simply too energy and time consuming. By indexing summary information obtained by a combination of multi-resolution analysis and k-means, our method (Hyper-Ad) is able to cut down the overall construction time of an overlay network such as CAN by an order of magnitude, as well as provide fast approximate similarity search on such a network. The results of our extensive experimental studies confirm that Hyper-M is both energy and time efficient, and provides good precision and recall.