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首页> 外文期刊>International journal of unconventional computing >Network Division Method Based on Cellular Growth and Physarum -inspired Network Adaptation
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Network Division Method Based on Cellular Growth and Physarum -inspired Network Adaptation

机译:基于细胞生长和受启发的网络适应的网络划分方法

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摘要

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.
机译:网络在现代世界无处不在,网络模型在科学,工程和通信中起着至关重要的作用。对于许多网络算法,处理时间随着节点数量的增加而呈指数增长,因此有必要对大型网络进行细分以实现计算可处理性,这是指网络划分。本文提出了一种基于细胞生长的网络划分方法。细胞生长的想法是受活生物体的生长和分裂机制启发的,网络适应的生物学动机是从粘液霉头cephal的觅食行为中采用的。在每个子网中,Physarum算法被用于网络结构设计中以最小化网络成本。使用具有1200个节点的服务器网络来测试所提出的生物启发式分割算法。该应用程序的结果说明了所提出方法的效率。

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