S-Cache: Function Caching for Serverless Edge Computing

Abstract

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.