Abstract. Peer-to-peer architectures are a potentially powerful model for developing large-scale networks of text-based digital libraries, but peer-to-peer networks have so far provided very limited support for text-based federated search of digital libraries using relevance-based ranking. This paper addresses the problems of resource representation, resource ranking and selection, and result merging for federated search of text-based digital libraries in hierarchical peer-to-peer networks. Existing approaches to text-based federated search are adapted and new methods are developed for resource representation and resource selection according to the unique characteristics of hierarchical peer-topeer networks. Experimental results demonstrate that the proposed approaches offer a better combination of accuracy and efficiency than more common alternatives for federated search in peer-to-peer networks.