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To acquire the network topology which is complex, unknown and continually changed, automatic discovery and automatic layout can be the best reliable and effective ways. Because of the huge number of nodes, connections, and circles in backbone network, the Force-directed placement model which is form the physical system is brought in to optimize visualization. In this model, network topology is auto-layout by random initiation and iterative adjustments. The FR (Fruchterman and Reingold) algorithm is improved to make the algorithm more suitable for backbone network topology auto-layout. By reevaluated the force function, the types and numbers of nodes can be identified for dynamic configuration. The placement can be edited and partly locked, and the crowded nodes are controlled in practice. The improvements and optimizations make it more available and adaptive in various networks. All the experimental data are derived from automatic discovery, which are authentic and practical.