Hybrid optical/electrical datacenter networks (HOE-DCNs) build inter-rack networks with both electrical Ethernet switches and optical cross-connects (OXCs), and have been considered as a promising DCN architecture. However, to adapt to the dynamic network environment, the reconfiguration of virtual networks (VNTs) in an HOE-DCN still faces the unique difficulty that the HOE-DCN's topology can change because of the one-to-one connectivity of OXCs. To the best of our knowledge, this problem still has not been fully explored. In this article, we address this problem, and consider how to achieve effective VNT reconfiguration in an HOE-DCN such that the IT resource usages in racks can be re-balanced with the migration of virtual machines (VMs). We first formulate a mixed integer linear programming (MILP) to describe the VNT reconfiguration. Then, we solve the problem with two steps, 1) obtaining the VM migration schemes to balance the loads on racks and 2) determining the reconfiguration schemes of related virtual links (VLs) and the OXC. For the first step, we propose a polynomial-time approximation algorithm by leveraging linear relaxation. Then, we tackle the optimization of the second step by developing an algorithm that involves a linear-time dynamic programming and an integer linear programming (ILP). To solve the ILP time-efficiently, we propose another polynomial-time approximation algorithm based on Lagrangian relaxation. Our simulations confirm the effectiveness of the proposed approximation algorithms and verify that the overall procedure including them outperforms the existing approach.

中文翻译：

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光/电混合数据中心网络中的虚拟网络重构


混合光/电数据中心网络（HOE-DCN）利用电气以太网交换机和光交叉连接（OXC）构建机架间网络，被认为是一种有前途的DCN架构。然而，为了适应动态网络环境，HOE-DCN中虚拟网络(VNT)的重新配置仍然面临着独特的困难，即由于OXC的一对一连接，HOE-DCN的拓扑可能会改变。据我们所知，这个问题仍未得到充分探讨。在本文中，我们将解决这个问题，并考虑如何在 HOE-DCN 中实现有效的 VNT 重新配置，以便机架中的 IT 资源使用可以随着虚拟机 (VM) 的迁移而重新平衡。我们首先制定混合整数线性规划（MILP）来描述 VNT 重新配置。然后，我们通过两个步骤解决问题，1）获取VM迁移方案以平衡机架上的负载，2）确定相关虚拟链路（VL）和OXC的重新配置方案。第一步，我们通过利用线性松弛提出了一种多项式时间近似算法。然后，我们通过开发一种涉及线性时间动态规划和整数线性规划（ILP）的算法来解决第二步的优化。为了高效地求解 ILP，我们提出了另一种基于拉格朗日松弛的多项式时间近似算法。我们的模拟证实了所提出的近似算法的有效性，并验证了包括它们的整个过程优于现有方法。