On Building a Self-Organizing Search System for Multimedia Retrieval

We focus on content-based retrieval in unstructured P2P networks consisting of thousands of peers that unpredictably join and leave the network. Such environments with permanent churning of peers require self-organizing mechanisms that should deal with sudden peer failures, arrivals of new peers, and continual changes of data or network topology. In this paper, we build a self-organizing search system that operates in an unstructured P2P network and allows users to search for multimedia data by their content. In order to efficiently route queries to relevant peers, we define and evaluate several techniques for joining new peers to the existing network. These techniques create new relationships between peers -- on the basis of answers returned to queries -- so that a new peer will be able to efficiently forward queries and other peers will be immediately informed about its data. In addition, we demonstrate resilience of the system to sudden peer failures by studying system performance and quality of returned answers after a large number of peers is disconnected. The experiments, evaluated on a synthetic and real-life multimedia dataset, confirm that the proposed techniques are suitable for dynamic environments.