U-HAUL: Efficient State Migration in NFV
U-HAUL: Efficient State Migration in NFV
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DOI：
10.1145/2967360.2967363
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发表时间：
2016-08
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影响因子：
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通讯作者：
Libin Liu;Hong Xu;Zhixiong Niu;Peng Wang;Dongsu Han
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作者：
Libin Liu;Hong Xu;Zhixiong Niu;Peng Wang;Dongsu Han
网络功能虚拟化（Network function virtualization， NFV）支持将资源动态扩展到中间件的部署和管理。在NFV中，状态迁移是一项重要的任务，因为运营商经常需要在NFV实例之间转移流量及其相关的流状态以实现负载平衡。然而，现有的状态迁移方案表现出较长的延迟和较高的控制器开销。提出了一种减少状态迁移开销的高效状态迁移系统U-HAUL。U-HAUL利用了这样一个事实，即大多数流都是短暂的鼠标流，在许多情况下，它们的处理状态将在状态迁移完成之前过期。U-HAUL并没有盲目地移动所有流的状态，而是将活动的老鼠流的状态保留在原始的NF实例上，而只迁移大象流的状态。通过减少需要迁移的流状态的数量，U-HAUL大大减少了迁移延迟和性能损失。我们的评估表明，与OpenNF相比，U-HAUL将平均迁移时间减少了87%，对小鼠流的延迟减少了94%。
Network function virtualization (NFV) enables dynamic scaling of resources to middlebox deployment and management. In NFV, state migration is an important task because operators often need to shift traffic and its associated flow states across NF instances for load balancing. Existing state migration schemes, however, exhibit long delays and high controller overhead. This paper presents U-HAUL, an efficient state migration system that reduces the state migration overhead. U-HAUL takes advantage of the fact that most flows are short-lived mice flows, and in many cases their processing states will expire before the state migration finishes. Rather than blindly moving states of all the flows, U-HAUL keeps the states of active mice flows on the original NF instance, and only migrates elephant flow states. By reducing the number of flow states to be migrated, U-HAUL greatly reduces the migration delay and its performance penalty. Our evaluation shows that U-HAUL reduces the average migration time by up to 87% and the latency to mice flows by up to 94% compared to OpenNF.