重新思考LTE网络功能虚拟化

M. T. Raza, Dongho Kim, Kyu-Han Kim, Songwu Lu, M. Gerla
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引用次数: 29

摘要

LTE网络功能虚拟化(LTE- nfv)通过将集中式传统LTE核心架构转换为分布式架构,以低成本的方式扩展用户服务。这种分布式体系结构使LTE网络功能(NFs)具有多个实例,并在商品数据中心网络上对它们进行虚拟化。然而,由于通过不可靠的IP链路连接的分布式NF实例延迟了关键事件的执行,LTE-NFV架构的功能被破坏了。时间关键事件的失效将导致用户的服务质量下降和暂时的服务不可用。本文提出了一种实现LTE核心网虚拟化的新方法。我们认为应该为NFV实现基于逻辑的NFs分离,而不是当前NFV实现中基于实例的NFs分离。我们的“基于逻辑的NFs隔离”方法将事件的逻辑合并到单个NF中,从而将关键事件的执行本地化到一个虚拟机中。这样,只有本地化的实体交换信令消息,事件不会经历大的延迟。利用LTE网络协议的并行性进一步降低时延;并对这些协议进行划分,使它们的信令消息并行运行。此外,我们消除了不必要的消息,以减少信令开销。我们在OpenEPC LTE核心网虚拟化平台上构建了系统原型。我们的结果表明,我们可以将事件执行时间和信号开销分别减少50%和40%。
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Rethinking LTE network functions virtualization
LTE Network Function Virtualization (LTE-NFV) scales user services in a low cost fashion by transforming the centralized legacy LTE Core architecture to a distributed architecture. This distributed architecture makes multiple instances of LTE Network Functions (NFs) and virtualizes them on commodity data-center network. The functionality of LTE-NFV architecture breaks however, since the distributed NF instances connected via unreliable IP links delay the execution of critical events. The failure of time-critical events results in users' quality of service degradation and temporary service unavailability. In this paper, we propose a new way to virtualize LTE core network. We argue that logic-based NFs segregation should be done for NFV, instead of instance-based NFs segregation done in current NFV implementation. Our approach of ‘logic-based NFs segregation’ combines the logic of an event into a single NF, thus localizing the execution of critical events to one virtual machine. This way, only the localized entities exchange signalling messages, and the events do not experience large delays. We further reduce the delays by exploiting the parallelism in LTE network protocols; and partition these protocols such that their signalling messages run in parallel. In addition, we eliminate unnecessary messages to reduce the signalling overhead. We build our system prototype over OpenEPC LTE core network in virtualized platform. Our results show that we can reduce event execution time and signalling overhead up to 50% and 40%, respectively.
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