A Cluster-based Hybrid Overlay Network for P2P Similarity Search

In this talk, I present a Hybrid Overlay Network (HON) for efficient similarity search in a P2P system. HON organizes both peers and data in an n-dimensional space based on content description. It is based on two key ideas. First it organizes and clusters peers in the n-dimensional feature space to limit flooding overhead and send queries only to relevant peers. Second, it organizes and places similar data objects in relatively dense regions of the feature space to achieve efficient processing of complex queries such as range and neighboring queries. Caching and dimensionality reduction mechanisms are considered in HON to improve its performance and maintain its scalability.