Edge Service Caching for Service Function Chains

Radhika Sukapuram, Sikha Deka
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Abstract

In Multi-access Edge Computing, services are hosted at the edge of the network to reduce latency and congestion. Services comprise Network Functions which provide security and optimize the network, and signalling and data processing functions. Services are chained to constitute Service Function Chains (SFCs). For latency critical applications or when the cloud is inaccessible, we posit that all the services of an SFC must be cached at the edge. Since services may be common across SFCs and require resources, the set of services to evict when the cache is full must be chosen such that as many SFCs as possible have all their services cached. We call this the SFC Cache Replacement Problem (SFC-CRP) and argue that measuring the service hit rate is insufficient. For the first time, we define the problem, quantity how to measure whether all the services of an SFC are cached at the edge and formulate it as an optimization problem. We implement the solution and demonstrate its effectiveness over a simple LRU heuristic by evaluations using datasets which we have derived from real (Alibaba) cluster traces.
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服务功能链的边缘服务缓存
在多接入边缘计算中,业务托管在网络的边缘,以减少延迟和拥塞。业务包括提供安全和优化网络的网络功能,以及信令和数据处理功能。服务被链接起来构成服务功能链(sfc)。对于延迟关键型应用程序或云不可访问时,我们假设SFC的所有服务都必须缓存在边缘。由于服务可能在sfc之间是通用的,并且需要资源,因此必须选择在缓存满时要退出的服务集,以便尽可能多的sfc缓存它们的所有服务。我们称之为SFC缓存替换问题(SFC- crp),并认为测量服务命中率是不够的。我们首次定义了如何度量一个SFC的所有服务是否被缓存到边缘的问题,并将其表述为一个优化问题。我们实现了该解决方案,并通过使用我们从真实(阿里巴巴)集群跟踪中获得的数据集进行评估,在一个简单的LRU启发式上证明了它的有效性。
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