Towards efficient virtual network embedding across multiple network domains
Towards efficient virtual network embedding across multiple network domains
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DOI：
10.1109/iwqos.2014.6914301
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发表时间：
2014-05
期刊：
影响因子：
--
通讯作者：
Meng Shen;Ke Xu;Kun Yang;Hsiao-Hwa Chen
中科院分区：
文献类型：
--
作者：
Meng Shen;Ke Xu;Kun Yang;Hsiao-Hwa Chen
网络虚拟化为在共享基础设施上同时运行多个虚拟网络(VN)提供了一种很有前途的方法。有效地将VNS映射到衬底资源上是至关重要的，这就是所谓的VN嵌入问题。现有的大多数研究将这一问题限制在单个衬底区域，而跨多个域的VN嵌入过程(即域间嵌入)更实用，因为单个域很少控制整个端到端路径。由于基础设施提供商(INP)通常不愿公开他们的底层信息，域间嵌入比域内嵌入更复杂。在本文中，我们提出了一种有效的解决方案来简化域间嵌入问题。我们首先通过使用类似于代理的角色--虚拟网络提供商(VNP)--来扩展当前的业务角色，以做出集中的嵌入决策。在此基础上，提出了一种合理的信息共享方案，为网络处理器提供部分衬底信息，同时保证网络处理器信息的保密性。然后我们将嵌入问题表示为一个整数规划问题。通过放松整数约束，我们设计了一种域间嵌入算法，能够在多项式时间内处理在线VN请求。仿真结果表明，在VNP完全了解所有衬底信息的理想场景下，我们的解决方案的性能优于其他同类方案，并实现了80%-90%的基准测试。
Network virtualization provides a promising way to run multiple virtual networks (VNs) simultaneously on a shared infrastructure. It is critical to efficiently map VNs onto substrate resources, which is known as the VN embedding problem. Most existing studies restrict this problem in a single substrate domain, whereas the VN embedding process across multiple domains (i.e., inter-domain embedding) is more practical, because a single domain rarely controls an entire end-to-end path. Since infrastructure providers (InPs) are usually reluctant to expose their substrate information, the inter-domain embedding is more sophisticated than the intra-domain case. In this paper, we develop an efficient solution to facilitate the inter-domain embedding problem. We start with extending the current business roles by employing a broker-like role, virtual network provider (VNP), to make centralized embedding decisions. Accordingly, a reasonable information sharing scheme is proposed to provide VNP with partial substrate information meanwhile keeping InPs' confidential information. Then we formulate the embedding problem as an integer programming problem. By relaxing integer constraints, we devise an inter-domain embedding algorithm to handle online VN requests in polynomial time. Simulation results show that our solution outperforms other counterparts and achieves 80%-90% of the benchmarks in an ideal scenario where VNP has complete knowledge of all substrate information.