重新分配虚拟网络嵌入以消除基板瓶颈

S. R. Chowdhury, Reaz Ahmed, Nashid Shahriar, Aimal Khan, R. Boutaba, J. Mitra, L. Liu
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引用次数: 17

摘要

网络虚拟化(NV)被认为是未来互联网的关键支持技术,它允许基础设施提供商(InP)通过从不同的服务提供商(sp)提供多个虚拟网络(VNs)来更好地利用其基板网络(SN)。虚拟网络嵌入的一个关键挑战是如何有效地将来自sp的虚拟网络请求映射到一个SN上,即虚拟网络嵌入(VNE)问题。VNE算法本质上通常是在线的。随着时间的推移,由于其他VN的到达和离开以及SN的变化(如故障),VN嵌入可能会变得次优。减轻这种动态影响的一种方法是定期为现有的虚拟网络重新分配资源。VNE的重新分配可以通过减少带宽消耗和增加接受未来vpn的可能性来增加InP的收入。本文研究了虚拟网络嵌入(ReViNE)的重新分配问题,以最小化网络上过度利用的底层链路数量和总带宽成本。我们提出了最优解的整数线性规划公式(ReViNE-OPT)和基于模拟退火的启发式方法(ReViNE-FAST)来解决更大的问题实例。仿真结果表明,我们提出的启发式算法平均在最优解的19%内执行。此外,与最先进的基于模拟退火的启发式VNE重新分配方法相比,ReViNE-FAST产生的解决方案要好2.5倍以上。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ReViNE: Reallocation of Virtual Network Embedding to eliminate substrate bottlenecks
Perceived as a key enabling technology for the future Internet, Network Virtualization (NV) allows an Infrastructure Provider (InP) to better utilize their Substrate Network (SN) by provisioning multiple Virtual Networks (VNs) from different Service Providers (SPs). A key challenge in NV is to efficiently map the VN requests from SPs on an SN, known as the Virtual Network Embedding (VNE) problem. VNE algorithms are typically online in nature. A VN embedding can become suboptimal over time due to the arrival and departure of other VNs as well as due to changes in SN such as failures. One way to mitigate the impact of such dynamism is to periodically reallocate resources for the existing VNs. VNE reallocation can increase an InP's revenue by decreasing bandwidth consumption and by increasing the possibility of accepting future VNs. In this paper, we study Reallocation of Virtual Network Embedding (ReViNE) problem to minimize the number of over utilized substrate links and total bandwidth cost on the SN. We propose an Integer Linear Programming formulation for the optimal solution (ReViNE-OPT) and a simulated annealing based heuristic (ReViNE-FAST) to solve larger problem instances. Simulation results show that on average our proposed heuristic performs within ∼19% of the optimal solution. Moreover, ReViNE-FAST generates more than 2.5× better solutions compared to the state-of-the-art simulated annealing based heuristic for VNE reallocation.
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