提出可微分无线网络数字孪生，实现高速精准调度优化
A Differentiable Digital Twin of Distributed Link Scheduling for Contention-Aware Networking
- 构建基于冲突图的可微分数字孪生模型，预测链路时隙占用率
- 在5000倍加速下准确预测时隙与拥塞模式，支持梯度下降优化
- 适合需要低延迟调度优化的无线多跳网络研究者使用
有线网络中的路由与流量优化问题可通过最小成本流方法高效求解，但该方法无法适用于无线多跳网络，因共享频谱资源导致的冲突使链路容量固定和成本线性等假设失效。无线链路的长期容量成为网络上下文（包括拓扑、链路质量及邻近链路流量）的非线性函数。本文通过随机介质访问控制建模无线网络，提出一种解析式网络数字孪生（NDT），从网络上下文预测链路时隙占用率。将随机竞争建模为在冲突图上使用加权Luby算法寻找最大独立集（MIS），推导出链路时隙占用率的解析模型，并引入迭代算法解决时隙占用率、链路容量与竞争概率之间的循环依赖。数值实验表明，所提NDT在高达5000倍于包级仿真的速度下仍能准确预测链路时隙占用率与拥塞模式，且支持梯度下降优化以降低拥塞和无线覆盖范围。
原文摘要 · Abstract (English)
Many routing and flow optimization problems in wired networks can be solved efficiently using minimum cost flow formulations. However, this approach does not extend to wireless multi-hop networks, where the assumptions of fixed link capacity and linear cost structure collapse due to contention for shared spectrum resources. The key challenge is that the long-term capacity of a wireless link becomes a non-linear function of its network context, including network topology, link quality, and the traffic assigned to neighboring links. In this work, we pursue a new direction of modeling wireless network under randomized medium access control by developing an analytical network digital twin (NDT) that predicts link duty cycles from network context. We generalize randomized contention as finding a Maximal Independent Set (MIS) on the conflict graph using weighted Luby's algorithm, derive an analytical model of link duty cycles, and introduce an iterative procedure that resolves the circular dependency among duty cycle, link capacity, and contention probability. Our numerical experiments show that the proposed NDT accurately predicts link duty cycles and congestion patterns with up to a 5000x speedup over packet-level simulation, and enables us to optimize link scheduling using gradient descent for reduced congestion and radio footprint.
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