Content-based video search on peer-to-peer networks

In this paper, we address the efficiency issue of the content-based video indexing over peer-to-peer (P2P) networks. The traditional video index is improved to suit with the P2P computational model. The algorithms to perform the video query based on the content similarity in the P2P environment are proposed. Also, the algorithms to handle the node joining, departure, index entry insertion are proposed. Furthermore, the load balancing approach based on the proposed algorithms is proposed. From the experiment results, our proposed approach outperforms a naive approach, which directly applies the P2P model with full replication, when a number of P2P nodes to be joined, as well as a number of videos to be inserted, is increased. Meanwhile, the efficiency of our approach in terms of the query answering is bounded by linear complexity. Moreover, our proposed load balancing approach is much more efficient than the naive approach in all experiments.