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Distributed Data Deluge (D3): Efficient state management for virtualized Network Functions

机译:分布式数据洪水(D3):虚拟化网络功能的高效状态管理

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The advent of Network Function Virtualization (NFV) opens up new opportunities for scaling out network function (NF) instances to meet evolving demands. However, dynamic NF scaling in conjunction with the highly unbalanced Internet traffic can induce a high degree of processing load imbalance among the NF instances. In this respect, we present Distributed Data Deluge (D3) for the distribution of processing load among the virtualized NF instances. D3 uses forwarding and NF internal state distribution to achieve load balancing and further retain it upon NF instance scale in/out or NF state corruption. To this end, D3 leverages on Distributed Hash Tables (DHT) for state distribution. Since DHT cannot cope with the unbalanced Internet traffic, we augment DHT with redundancy and a flow handover mechanism. We further discuss techniques for detection and recovery from NF state corruption. Finally, we assess the load balancing efficiency of D3, using trace-driven simulations.
机译:网络功能虚拟化(NFV)的出现为扩展网络功能(NF)实例以满足不断发展的需求提供了新的机会。但是,动态NF缩放与高度不平衡的Internet流量结合会在NF实例之间引起高度的处理负载不平衡。在这方面,我们提出了用于在虚拟化NF实例之间分配处理负载的分布式数据洪水(D3)。 D3使用转发和NF内部状态分配来实现负载平衡,并在NF实例扩展/扩展或NF状态损坏时进一步保持负载平衡。为此,D3利用分布式哈希表(DHT)进行状态分配。由于DHT无法应对不平衡的Internet流量,因此我们通过冗余和流切换机制来增强DHT。我们进一步讨论了用于检测和从NF状态损坏中恢复的技术。最后,我们使用跟踪驱动的模拟评估D3的负载平衡效率。

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