Mathematical Model for Reducing Complex Network Topology Using Graphs and Labeling with Hamiltonian
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Abstract
Complex networks are prevalent in various fields such as communication systems, social networks, and biological networks. Managing and analysing these networks can be challenging due to their intricate topology. In this paper, we propose a mathematical model for reducing complex network topology using Dynamic Mode-M graphs and labelling with Isomorphic Square Pattern Cordial Graph (ISPCG). The path definition is analysed with cross vertex Exchange cubic Hamiltonian path (Cv-ECHP) to connect the least distance neighbour nodes in the routing to reduce the topology complexity. The proposed system simplifies the analysis of complex networks data transmission and improve efficiency in routing enrichment.
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