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 while pruning nodes that do not significantly contribute to the range query resolution. Removing nonproductive nodes reduces the cost (e.g., hops and latency) of advertising resources and resolving queries. Second and third heuristics dynamically balance the key and query load distribution by transferring some of the keys to its predecessor/successor and by adding new predecessors/successors to handle transferred keys when existing nodes are insufficient, respectively. Last two heuristics form cliques of nodes (that are placed orthogonal to the overlay ring) to dynamically balance the highly skewed key and query loads. By applying these heuristics in the presented order, a RD solution that better responds to real-world resource and query characteristics is developed. Its efficacy is demonstrated using a simulation-based analysis under a variety of single and multi-attribute resource and query distributions derived from real workloads
