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Distributed, multi-attribute Resource Discovery (RD) is a fundamental requirement in collaborative Peer-to-Peer (P2P), grid, and cloud computing. We present an efficient and load balanced, P2P-based multi-attribute RD solution that consists of five heuristics, which can be executed independently and distributedly. First heuristic maintains a minimum number of nodes in a ring-like overlay consequently reducing the cost of resolving range queries. Second and third heuristics dynamically balance the key and query load by transferring keys to neighbors and by adding new neighbors when existing ones are insufficient. Last two heuristics, namely fragmentation and replication, form cliques of nodes that are placed orthogonal to the overlay ring to dynamically balance the highly skewed key and query loads while reducing the query cost. By applying these heuristics in the presented order, a RD solution that better responds to real-world resource and query characteristics is developed. Simulations using real workloads are used to demonstrate its efficacy.