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A Benders Decomposition Approach for Resilient Placement of Virtual Process Control Functions in Mobile Edge Clouds

机译:一种在移动边缘云中弹性放置虚拟过程控制功能的Benders分解方法

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Replacing hardware controllers with software-based virtual process control functions (VPFs) is a promising approach for improving the operational efficiency and flexibility of industrial control systems. VPFs can be executed in edge clouds in 5G mobile networks or in the wireless backhaul, which can further improve efficiency. Nonetheless, for the acceptance of virtualization in industrial control systems, a fundamental challenge is to ensure that the placement of VPFs be resilient to component failures and cyber-attacks, besides being efficient. In this paper we address this challenge by considering that VPF placement costs are incurred by reserving mobile edge computing (MEC) resources, executing VPF instances, and by data communication. We formulate the VPF placement problem as an integer programming problem, considering resilience as a constraint. We propose a solution based on generalized Benders decomposition and based on linear relaxation of the resulting sub-problems, which effectively reduces the number of integer variables to the number of MEC nodes. We evaluate the proposed solution with respect to operational cost, efficiency, and scalability in a simulated metropolitan area. Our results show that the proposed solution reduces the total cost significantly compared to a greedy baseline algorithm and a local search heuristic, and can scale to moderate problem instances.
机译:用基于软件的虚拟过程控制功能(VPF)替换硬件控制器是提高工业控制系统的运行效率和灵活性的一种有前途的方法。 VPF可以在5G移动网络的边缘云中或在无线回程中执行,这可以进一步提高效率。尽管如此,要在工业控制系统中接受虚拟化,一个基本的挑战是确保VPF的放置除了具有效率之外,还可以抵抗组件故障和网络攻击。在本文中,我们通过考虑通过保留移动边缘计算(MEC)资源,执行VPF实例以及进行数据通信而产生的VPF放置成本来应对这一挑战。我们将弹性系数作为约束条件,将VPF放置问题公式化为整数规划问题。我们提出了一种基于广义Benders分解和所得子问题的线性松弛的解决方案,该解决方案有效地将整数变量的数量减少到MEC节点的数量。我们评估拟议的解决方案在模拟大都市地区的运营成本,效率和可扩展性方面。我们的结果表明,与贪婪的基线算法和局部搜索启发式算法相比,提出的解决方案显着降低了总成本,并且可以扩展到中等问题实例。

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