Context-aware Container Orchestration in Serverless Edge Computing

Abstract

Adopting serverless computing to edge networks benefits end-users from the pay-as-you-use billing model and flexible scaling of applications. This paradigm extends the boundaries of edge computing and remarkably improves the quality of services. However, due to the heterogeneous nature of computing and bandwidth resources in edge networks, it is challenging to dynamically allocate different resources while adapting to the high burstiness and concurrency in serverless workloads. This article focuses on serverless function provisioning in edge networks with the aim of optimizing end-to-end latency, where the challenge lies in jointly allocating wireless bandwidth and computing resources among heterogeneous computing nodes. We devise a context-aware learning framework that adaptively orchestrates a wide spectrum of resources and jointly considers them to avoid resource fragmentation. Extensive simulation results justify that the proposed algorithm saves over 95% of converge time, and the total delay is almost the same level as the state of the art.