S-Cache: Function Caching for Serverless Edge Computing
S-Cache: Function Caching for Serverless Edge Computing
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DOI：
10.1145/3578354.3592865
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发表时间：
2023-05
期刊：
影响因子：
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通讯作者：
Cheng Chen;Lars Nagel;Lin Cui;Fung Po Tso
中科院分区：
文献类型：
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作者：
Cheng Chen;Lars Nagel;Lin Cui;Fung Po Tso
无服务器边缘计算使用事件驱动的模型，其中物联网 (IoT) 服务仅在调用时才在短暂的无状态容器中运行，从而显着降低资源利用率。然而，容器的冷启动可能需要长达几秒钟的时间，这会显着降低无服务器应用程序的响应时间。容器缓存可以缓解冷启动问题，但代价是额外的计算资源，这违背了无服务器计算的精神。因此，我们需要平衡冷启动开销和无服务器边缘计算的额外资源利用率。然而，容器的不同范围导致了不同的冷启动开销、资源消耗和调用频率，而容器的这些特性在很大程度上被现有的缓存策略所忽视。在本文中，我们研究无服务器边缘计算的请求分发和缓存问题。我们设计了一种具有性能保证的在线请求分发算法，并提出了一种结合容器频率、容器大小和冷启动时间的自适应缓存策略。通过实际系统实现，通过与现有缓存策略（包括固定缓存和基于直方图的策略）的比较，验证了该算法的优越性。我们的结果表明，与当前方法相比，所提出的算法将平均响应时间和冷启动频率减少了 3 倍。
Serverless edge computing uses an event-driven model in which Internet-of-Things (IoT) services are run in short-lived, stateless containers only when invoked, leading to significant reduction of resource utilization. However, a cold-start of a container can take up to several seconds which significantly degrades the response time of serverless applications. Container caching can mitigate the cold-start problem at the cost of extra computing resources which violates the spirit of serverless computing. Therefore, we need to balance the cold-start overheads with the extra resource utilization for serverless edge computing. Nevertheless, the diverse ranges of containers lead to different cold-start overheads, resource consumption and invocation frequencies and these characteristics of containers are largely overlooked by existing caching policies. In this paper, we study the request distribution and caching problem for serverless edge computing. We devise an online request distribution algorithm with performance guarantee and present an adaptive caching policy which incorporates container frequency, container size and cold-start time. Via real-system implementation, the superiority of the proposed algorithm is verified by comparing with existing caching policies, including fixed caching and histogram based policies. Our results show that the proposed algorithm reduces both the average response time and cold-start frequency by a factor of 3 compared to current approaches.