The efficiency of service discovery is a crucial point in the development of fully decentralized middlewares intended to manage large scale computational grids. The work conducted on this issue led to the design of many peer-to-peer fashioned approaches. More specifically, the need for flexibility and complexity in the service discovery has seen the emergence of a new kind of overlays, based on tries, also known as lexicographic trees. Although these overlays are efficient and well designed, they require a costly maintenance and do not accurately take into account the heterogeneity of nodes and the changing popularity of the services requested by users. In this paper, we focus on reducing the cost of the maintenance of a particular architecture, based on a dynamic prefix tree, while enhancing it with some load balancing techniques that dynamically adapt the load of the nodes in order to maximize the throughput of the system. The algorithms developed couple a self-organizing prefix tree overlay with load balancing techniques inspired by similar previous works undertaken for distributed hash tables. After some simulation results showing how our load balancing heuristics perform in such an overlay and compare to other heuristics, we provide a fair comparison of this architecture and similar overlays recently proposed.