Elastic Scaling of Stateful Network Functions
Elastic Scaling of Stateful Network Functions
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发表时间：
2018-04
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通讯作者：
S. Woo;Justine Sherry;Sangjin Han;S. Moon;Sylvia Ratnasamy;S. Shenker
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作者：
S. Woo;Justine Sherry;Sangjin Han;S. Moon;Sylvia Ratnasamy;S. Shenker
弹性伸缩是NFV的核心承诺，但在实践中很难实现。困难的出现是因为大多数网络功能（NF）是有状态的，并且这种状态需要在NF实例之间共享。在满足对NF的吞吐量和延迟要求的同时实现状态共享是具有挑战性的，并且迄今为止，不存在满足针对NF的全谱的NFV的性能目标的解决方案。S6是一个新的框架，它支持NF的弹性扩展，而不会影响性能。它的设计基于分布式共享状态抽象非常适合NFV上下文的见解。我们将状态组织为分布式共享对象（DSO）空间，并使用旨在满足NFV工作负载弹性和高性能需求的技术扩展DSO概念。S6简化了开发：NF编写器程序不知道状态是如何分布和共享的。相反，S6透明地迁移状态并处理对共享状态的访问。在我们的评估中，与最近的NF动态缩放解决方案相比，S6在缩放事件期间将性能提高了100倍[2 - 5]，在正常操作下提高了2- 5倍[27]。
Elastic scaling is a central promise of NFV but has been hard to realize in practice. The difficulty arises because most Network Functions (NFs) are stateful and this state need to be shared across NF instances. Implementing state sharing while meeting the throughput and latency requirements placed on NFs is challenging and, to date, no solution exists that meets NFV’s performance goals for the full spectrum of NFs. S6 is a new framework that supports elastic scaling of NFs without compromising performance. Its design builds on the insight that a distributed shared state abstraction is well-suited to the NFV context. We organize state as a distributed shared object (DSO) space and extend the DSO concept with techniques designed to meet the need for elasticity and high-performance in NFV workloads. S6 simplifies development: NF writers program with no awareness of how state is distributed and shared. Instead, S6 transparently migrates state and handles accesses to shared state. In our evaluation, compared to recent solutions for dynamic scaling of NFs, S6 improves performance by 100x during scaling events [25], and by 2-5x under normal operation [27].