Innovative dual-factor network assessment: topology & traffic

Network security has always been the focus of Internet research. In order to better detect these attacks, it is necessary to more accurately evaluate the state performance of the network. The existing measurement methods often only focus on a single or very few indicators.

To solve the problems, a research team led by Cheng Guang and Qi Shengyuan  published their new research on 15 November 2025 in Frontiers of Computer Science co-published by Higher Education Press and Springer Nature.

The team proposed an A network integrated performance evaluation method based on multi-attribute decisions of topic and traffic. The proposed evaluation algorithm assesses network effectiveness, importance, and reliability by integrating multiple dimensions. This multi-metric approach ensures adaptability across various network environments.  And the effectiveness of the method was demonstrated through experiments

In the research, the proposed evaluation algorithm assesses network effectiveness, importance, and reliability by integrating multiple dimensions. Effectiveness measures the relationship between actual traffic and maximum capacity. Node importance is quantified using eigenvector centrality and neighboring node similarity, while link importance is evaluated through subgraphs using the reliability polynomial method. Reliability is assessed based on node and link stability and resilience. Finally, these different dimensions of data are unified together through TOPSIS multi data decision-making, and NIP is used to measure the overall performance of the network.



This paper presents a novel network performance evaluation method that integrates topology and traffic through multi-attribute decision-making. It assesses the effectiveness, importance, and reliability of nodes and links, adapting to traffic changes. The method combines node and link attributes for a comprehensive performance evaluation, validated through simulations and attack tests, demonstrating its practical relevance for network management and security. The system can also adjust transmission paths in real-time based on these evaluations, especially during emergencies.