Celestial Equilibrium Theory-Based Optimal Deployment of SRv6 for Traffic Engineering

Segment Routing over IPv6 (SRv6) is a promising source routing solution with wide-ranging applications in the field of Traffic Engineering. By adding SR tags into IPv6 packets, traffic can be directed to various SR segments, effectively distributing traffic. However, upgrading all network nodes to SRv6 nodes simultaneously is impractical. This paper addresses the incremental deployment of SRv6 from traffic engineering, aiming to minimize MLU within the network. We introduce the theory of celestial equilibrium and model the problem as a celestial equilibrium-like model with a global distribution of SR nodes and their corresponding areas of influence. To address this problem model, we propose a novel algorithm based on the EM algorithm, EM-SRTE. In our proposed framework, step E leverages a reinforcement learning algorithm combined with a self-attention module for graph learning to optimize the selection of SR nodes. Meanwhile, step M utilizes a similar algorithm to optimize the region range of SR nodes. Experimental results using publicly available datasets demonstrate that our model outperforms state-of-the-art baselines.