一种虚拟网络业务管理的约束最短路径方案
A Constrained Shortest Path Scheme for Virtual Network Service Management
摘要：
跨多个数据中心的虚拟网络服务对于支持生物信息学和零售分析等领域的新兴数据密集型应用非常重要。成功的虚拟网络服务组合和维护需要在用于虚拟网络嵌入（VNE）或网络功能虚拟化服务链（NFV-SC）的管理平面中以及在用于流量工程（TE）的数据平面中的灵活且可扩展的“约束最短路径管理”。在本文中，我们通过分析和经验表明，利用最近的VNE，NFV-SC和TE算法中的约束最短路径可以导致网络利用率增益（高达50%）和更高的能源效率。然而，复杂的VNE，NFV-SC和TE算法的管理，可以是棘手的大规模基板网络，由于NP-困难的约束最短路径问题。为了解决这种可扩展性的挑战，我们提出了一种新的，精确的约束最短路径算法，即，“邻域方法”（NM）。我们的NM使用新的搜索空间减少技术，并有一个理论上的二次加速，使其实际上更快（由一个数量级）比最近的分支和界穷举搜索解决方案。最后，我们详细介绍了我们的基于网络管理的SDN控制器在现实世界的测试平台，以进一步验证虚拟网络服务的实际NM的好处。
英文摘要：
Virtual network services that span multiple data centers are important to support emerging data-intensive applications in fields such as bioinformatics and retail analytics. Successful virtual network service composition and maintenance requires flexible and scalable 'constrained shortest path management' both in the management plane for virtual network embedding (VNE) or network function virtualization service chaining (NFV-SC), as well as in the data plane for traffic engineering (TE). In this paper, we show analytically and empirically that leveraging constrained shortest paths within recent VNE, NFV-SC and TE algorithms can lead to network utilization gains (of up to 50%) and higher energy efficiency. The management of complex VNE, NFV-SC and TE algorithms can be, however, intractable for large scale substrate networks due to the NP-hardness of the constrained shortest path problem. To address such scalability challenges, we propose a novel, exact constrained shortest path algorithm viz., 'Neighborhoods Method' (NM). Our NM uses novel search space reduction techniques and has a theoretical quadratic speed-up making it practically faster (by an order of magnitude) than recent branch-and-bound exhaustive search solutions. Finally, we detail our NM-based SDN controller implementation in a real-world testbed to further validate practical NM benefits for virtual network services.
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