As one of the key focuses in 6G research, the space–air–ground integrated network incorporates a variety of technological frameworks. Network function virtualization allows network functions to be deployed on general servers in the form of software and creates a service function chain (SFC) according to user service requirements. In recent years, the deployment of SFC has become popular research due to the increasing demand for low delay in network application scenarios. Low delay is a crucial indicator of the quality of service, especially for delay-sensitive applications. To address this issue, we propose a method for the deployment of delay-sensitive SFC based on parallelization and the improved cuckoo search (ICS) algorithm (DDSSFC-PICS). This method optimizes the composition and deployment of SFC jointly. First, the serial structure of the SFC is transformed into a parallel structure by determining the dependency of virtual network functions, which reduces the length of the SFC and thereby reduces delay. Second, with the optimization goal of minimizing network delay, a parallel SFC deployment model is established under constraints including packet loss rate and resource availability. Finally, the ICS algorithm is applied for optimization, where delay is used as the fitness measure. By improving the Lévy flight step size and drawing inspiration from the whale algorithm, the performance of the cuckoo search (CS) algorithm is enhanced, leading to a further reduction in delay. The simulation results show that using the same CS deployment method, parallelized SFC has a significantly lower delay compared to serial SFC. Furthermore, the DDSSFC-PICS reduces the delay by 22.58% and 19.02%, respectively, compared with the CS deployment and particle swarm optimization SFC deployment methods.

中文翻译：

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基于并行化和改进布谷鸟搜索算法的时延敏感服务功能链智能部署

天地一体化网络作为6G研究的重点之一，融合了多种技术框架。网络功能虚拟化允许网络功能以软件的形式部署在通用服务器上，并根据用户业务需求创建服务功能链（SFC）。近年来，由于网络应用场景对低时延的需求不断增加，SFC的部署成为热门研究。低延迟是服务质量的关键指标，特别是对于延迟敏感的应用程序。为了解决这个问题，我们提出了一种基于并行化和改进的布谷鸟搜索（ICS）算法（DDSSFC-PICS）的延迟敏感SFC的部署方法。该方法联合优化了SFC的组成和部署。第一的，通过确定虚拟网络功能的依赖关系，将SFC的串行结构转变为并行结构，减少了SFC的长度，从而减少延迟。其次，以网络时延最小化为优化目标，在丢包率、资源可用性等约束下建立并行SFC部署模型。最后，应用ICS算法进行优化，其中延迟被用作适应度度量。通过改进Lévy飞行步长并从鲸鱼算法中汲取灵感，增强了布谷鸟搜索（CS）算法的性能，从而进一步减少了延迟。仿真结果表明，采用相同的CS部署方式，并行SFC相比串行SFC具有明显更低的延迟。此外，