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The present paper proposes a parallel evolutionary P2P networking technique (P-EP2P) that applies an evolutionary networking technique (EP2P) in parallel to small networks into which an entire P2P network is divided. EP2P dynamically and adaptively optimizes several P2P network topologies, in which all of the nodes are included at the same time, in an evolutionary manner. However, EP2P has a scalability problem that load is more concentrated in a particular node as the number of nodes increases. The aim of P-EP2P is to first balance load among the nodes to maintain the function of the entire network and then bring adaptability even to a large-scale P2P network. Simulation results reveal that P-EP2P is capable of balancing load among the nodes, but degrades search reliability as the number of the small networks increases, which indicates that there is a trade-off relationship between the load balancing and the search reliability. The results suggest that to enhance the search reliability, the small networks should exchange information among them to maintain consistency of the network topologies, though that causes additional load to the nodes.