面向软件定义网络的可变粒度数字孪生构建技术

Variable granularity digital twin construction technology for software defined network

软件定义网络(software defined network,SDN)应用范围的扩大带来了应用需求多样化的挑战。利用数字孪生(digital twin,DT)增强SDN的实时分析、推演和控制能力,能更好地满足各种应用场景需求。然而,当前SDN的数字孪生构建面临着时延需求高、计算开销大、资源协调难的问题。因此,以应用需求为导向,在网络可用计算资源约束下,提出了一种新型的可变粒度数字孪生(variable granularity digital twin,VGDT)思想及其构建技术。VGDT结合网络可用计算资源分布特征,建立了保证数字孪生时延和完整度的多节点资源协同优化模型。在此基础上,利用混合编码遗传算法对该模型进行求解,获得最佳映射数据粒度和数字孪生部署方案,指导数字孪生的构建过程。仿真结果表明,与现有模式相比,在网络计算资源约束下,VGDT具有更高的数字孪生模型完整度和有效性。

As SDN is increasingly widely used in various scenarios,a new challenge for SDN to support dynamic requirements of various applications begin to emerge.DT can enhance the capabilities of SDN in aspects of real-time analysis,deduction,and network control,and consequently satisfy the dynamic requirements of various applications.Whereas,current DT constructing schemes for SDN usually suffer from the challenges of strict delay constraint,heavy computing overhead,and low cooperating efficiency.To address the above issue,this paper proposed a novel variable granularity-digital twin(VGDT)accor-ding to the application requirement and available computing resource.Based on the distribution characteristic of the computing resource in the network,VGDT built a cooperatively optimizing model to ensure the delay and effectiveness of the DT for SDN.Then,this paper proposed a hybrid coding genetic algorithm to solve this model,which could achieve the best granularity and the DT placement policy.The simulation results show the performance of VGDT.Compared with current DT,VGDT has higher integrity and validity of digital twin model under limited computing resource.