Revenue-Oriented Optimal Service Offloading Based on Fog-Cloud Collaboration in SD-WAN Enabled Manufacturing Networks

IF 6.7 2区计算机科学 Q1 ENGINEERING, MULTIDISCIPLINARY

IEEE Transactions on Network Science and Engineering Pub Date : 2025-01-15 DOI:10.1109/TNSE.2025.3526750

Xu Chen;Yi Zhang;Chunxiao Jiang;Changqiao Xu;Zhenhui Yuan;Gabriel-Miro Muntean

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引用次数: 0

Abstract

The software-defined wide area network (SD-WAN) is considered one of the most promising paradigms for next generation manufacturing networks. However, SD-WAN users usually suffer from significant delays due to remotely deployed cloud centers. The requirements of delay-sensitive business services make optimal resource allocation methods very important. In this paper, we propose a revenue-oriented service offloading method to improve the efficiency of SD-WAN enabled manufacturing networks through fog-cloud collaboration. To maximize the service revenue, we formulate a coupled combinatorial optimization model to allocate computation and communication resources jointly between the fog node and the cloud. To solve this problem, we propose a service offloading method based on the counterfactual regret minimization (CFR) principle according to the dynamic workload state of the fog nodes. This method reduces the time complexity of problem-solving from exponential to polynomial, and achieves good performance that is very close to the optimal solution in terms of service efficiency. The outstanding contribution of this paper is to unify the multi-objective problem to the revenue scale for optimization to improve the overall service revenue of the SD-WAN. The simulation results show that our method outperforms benchmark methods in terms of both effectiveness and efficiency.

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在支持 SD-WAN 的制造网络中基于雾-云协作的以收益为导向的优化服务卸载

软件定义广域网（SD-WAN）被认为是下一代制造网络最有前途的范例之一。然而，由于远程部署的云中心，SD-WAN用户通常会遭受严重的延迟。对延迟敏感的业务服务的需求使得优化资源分配方法变得非常重要。在本文中，我们提出了一种以收入为导向的服务卸载方法，通过雾云协作来提高SD-WAN制造网络的效率。为了使服务收益最大化，我们建立了一个耦合组合优化模型，在雾节点和云之间共同分配计算资源和通信资源。为了解决这一问题，我们根据雾节点的动态工作状态，提出了一种基于反事实遗憾最小化（CFR）原则的服务卸载方法。该方法将问题求解的时间复杂度从指数型降低到多项式型，并且在服务效率方面取得了非常接近最优解的良好性能。本文的突出贡献在于将多目标问题统一到收益规模上进行优化，从而提高SD-WAN的整体业务收益。仿真结果表明，该方法在有效性和效率方面都优于基准方法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Transactions on Network Science and Engineering Engineering-Control and Systems Engineering

CiteScore

12.60

自引率

9.10%

发文量

393

期刊介绍： The proposed journal, called the IEEE Transactions on Network Science and Engineering (TNSE), is committed to timely publishing of peer-reviewed technical articles that deal with the theory and applications of network science and the interconnections among the elements in a system that form a network. In particular, the IEEE Transactions on Network Science and Engineering publishes articles on understanding, prediction, and control of structures and behaviors of networks at the fundamental level. The types of networks covered include physical or engineered networks, information networks, biological networks, semantic networks, economic networks, social networks, and ecological networks. Aimed at discovering common principles that govern network structures, network functionalities and behaviors of networks, the journal seeks articles on understanding, prediction, and control of structures and behaviors of networks. Another trans-disciplinary focus of the IEEE Transactions on Network Science and Engineering is the interactions between and co-evolution of different genres of networks.