Resource discovery is critical to the usability and accessibility of grid computing systems. Distributed Hash Table (DHT) has been applied to grid systems as a distributed mechanism for providing scalable range-query and multiattribute resource discovery. Multi-DHT-based approaches depend on multiple DHT networks with each network responsible for a single attribute. Single-DHT-based approaches keep the resource information of all attributes in a single node. Both classes of approaches lead to high overhead. Recently, we proposed a heuristic Low-Overhead Range-query Multiattribute DHT-based resource discovery approach (LORM). It relies on a single hierarchical DHT network and distributes resource information among nodes in balance by taking advantage of the hierarchical structure. We demonstrated its effectiveness and efficiency via simulation. In this paper, we analyze the performance of the LORM approach rigorously by comparing it with other multi-DHT-based and single-DHTbased approaches with respect to their overhead and efficiency. The analytical results are consistent with simulation results. The results prove the superiority of the LORM approach in theory