Ekko: Fully Decentralized Scheduling for Serverless Edge Computing

Abstract

While originally designed for the cloud, the benefits of the serverless paradigm are vital in Edge/Fog computing environments. In this paper, we propose Ekko, a novel decentralized edge serverless scheduling system, which enables a large number of serverless applications to run simultaneously at the edge through the Functionas-a-Service (FaaS) model. The key insight is to re-architect the common centralized or hierarchical scheduling systems into a fully decentralized one by using the distributed hash table (DHT) based peer-to-peer (P2P) model, in which many distributed schedulers operate autonomously without any centralized state. In sharp contrast to existing studies, any edge node in our system can act as a scheduler, a function worker, a query forwarder, or a storage node, and flexibly switch between these roles, thereby significantly improving scalability and adaptivity. Ekko introduces three design innovations: a boundary-aware P2P organization, distributed shadow schedulers with a keychain scheduling algorithm, and a distributed locality-aware bucket image store. Our evaluation on 500 Amazon EC2 nodes shows that, compared to the state-of-the-art, Ekko reduces the 90-th percentile tail queue wait time by up to 96.6 %, the scheduling time by up to 38.5 %, and the total deployment time by up to 89.5 %, while efficiently scaling to millions of function invocation requests on thousands of edge nodes.