Behavior Tree-Based Network Function Extension Framework for Enhancing Flexibility and Scalability
Huang, Jiaorui Yang, Chungang Feng, Tao Guan, Jianfeng Dong, Lujia Shen, Ao Li, Yuanyuan Huang, Tao Guizani, Mohsen
Huang, Jiaorui
Yang, Chungang
Feng, Tao
Guan, Jianfeng
Dong, Lujia
Shen, Ao
Li, Yuanyuan
Huang, Tao
Guizani, Mohsen
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Department
Machine Learning
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Journal article
Date
2025
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English
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Abstract
With the rapid development of the Internet, users are demanding a wide range of diverse network functions, for instance, security and delay. Consequently, there is a promising need for networks to transition towards softwarization, virtualization, and containerization to better meet these growing demands. However, due to the inherent design of conventional networks, expanding and managing network functions remains challenging. Conventional networks often require switch node reboots to install and expand network functions, leading to transmission interruptions and low efficiency. Behavior trees, characterized by their modularity, extensibility, and high readability, provide an effective solution for expanding on-demand network functions. This article presents a behavior tree-based network function extension framework (BTNF) that enhances flexibility and scalability. Based on this framework, we propose a behavior tree-based seepage, which is a routing protocol that dynamically adapts to network conditions. This protocol replaces the finite state machine mechanism of conventional routing protocols, constructing the internal logic processes to achieve reliable packet transmission. Finally, we provide a proof-of-concept implementation prototype to validate the feasibility and effectiveness of the proposed BTNF framework.
Citation
J. Huang et al., "Behavior Tree-Based Network Function Extension Framework for Enhancing Flexibility and Scalability," in IEEE Network, doi: 10.1109/MNET.2025.3601612
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IEEE Network
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IEEE