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Network Division Method Based on Cellular Growth and Physarum-inspired Network Adaptation
Hanchao Yang, Yong Deng and Jeff Jones

Networks are ubiquitous in the modern world and network models play an essential part in science, engineering and communications. For many network algorithms, the processing time grows exponentially as the number of nodes increases, making it necessary to subdivide large networks for computational tractability, which refers to the network division. In this paper, a network division method based on cellular growth is proposed. The cellular growth idea was inspired by growth and division mechanisms in living organisms, and the biological motivation of network adaptation was adopted from the foraging behaviour of slime mould Physarum polycephalum. Within each subnetwork, Physarum algorithm was adopted in network structure design to minimize network cost. A server network with 1200 nodes was used to test the proposed bio-inspired division algorithm. The result of this applications illustrates the efficiency of the proposed method.

Keywords: Network division, bio-inspired model, physarum algorithm, cellular growth

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