Optimizing Cost-Efficient SFC Routing in NTNs: A Novel Transformer-Ant Colony Optimization Framework
Yuanfeng Li, Qi Zhang, Haipeng Yao, Xiangjun Xin, Yi Zhao, Ran Gao
Abstract
Non-Terrestrial Networks (NTN), including Low Earth Orbit (LEO) satellite constellations, aim to provide connectivity to remote and underserved areas. These networks now support complex network services leveraging Service Function Chaining (SFC), which sequences service functions such as firewalls and load balances to customize network behavior. In this paper, a comprehensive system model for SFC deployment in NTN is presented. The SFC deployment problem is regarded as comprising two parts: routing and VNF embedding. To improve the cost efficiency of SFC deployment in NTN, a Transformer-Ant Colony Optimization approach has been proposed. The employment of the Transformer architecture to encode SFC requests and the assistance of ACO with neural network modules in identifying optimal paths for VNF embedding are pioneered in this work. The simulation results confirm that our approach achieves superior performance in terms of cost, communication success rate, and delay, demonstrating its potential for efficient SFC deployment in NTN scenarios.