Optimization Method for Robustness of Hypernetwork Communication with Integrated Structural Features
Lei Chen, Xiujuan Ma, Fuxiang Ma
TL;DR
This paper introduces a new optimization method to improve the communication robustness of hypernetworks by integrating structural features.
Contribution
A novel optimization method for hypernetwork communication robustness using four structural indicators is proposed and validated.
Findings
Hyper-betweenness centrality provides the most significant improvement in communication robustness.
The proposed method is effective across BA, ER, and NW hypernetwork models.
The optimization method successfully enhances robustness in the WIKI-VOTE social hypernetwork.
Abstract
The ultimate objective of research on hypernetwork robustness is to enhance its capability to withstand external attacks and natural disasters. For hypernetworks such as telecommunication networks, public safety networks, and military networks—where security requirements are extremely high—achieving higher communication robustness is essential. This study integrates the structural characteristics of hypernetworks with an optimization method for communication robustness by combining four key indicators: hyper-betweenness centrality, hyper-centrality of feature subgraph, hyper-centrality of Fiedler, and hyperdistance entropy. Using the best improvement performance (BIP_T) as the evaluation metric, simulation experiments were conducted to comparatively analyze the effectiveness of these four indicators in enhancing the communication robustness of Barabási–Albert (BA), Erdos–Renyi (ER), and…
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Taxonomy
TopicsSoftware-Defined Networks and 5G · Complex Network Analysis Techniques · Advanced MIMO Systems Optimization