Peer-to-peer (P2P) networks integrate autonomous computing resources without requiring a central coordinating authority, which makes them a potentially robust and scalable model for providing federated search capability to large-scale networks of text-based digital libraries. However, peer-to-peer networks have so far provided very limited support for full-text federated search with relevance-based document ranking. This paper provides solutions to full-text federated search of text-based digital libraries in hierarchical peer-to-peer networks. Existing approaches to full-text search are adapted and new methods are developed for the problems of resource representation, resource selection, and result merging according to the unique characteristics of hierarchical peer-to-peer networks. Experimental results demonstrate that the proposed approaches offer a better combination of accuracy and efficiency than more common alternatives for federated search of text-based digital libraries in peer-to-peer networks.