ClusterLess: Deadline-Aware Serverless Workflow Orchestration on Federated Edge Clusters

Abstract

The recent convergence of edge computing, serverless execution, and Kubernetes (K8s)-based container orchestration has enabled the processing of application workflows close to data sources. While effective within a single-edge cluster, existing schemes do not generalize to federated multi-edge environments, where multiple workflows execute concurrently under strict end-to-end (E2E) deadline constraints. This paper introduces ClusterLess, a deadline-aware serverless workflow orchestration method for federated multi-edge K8s clusters. ClusterLess manages the E2E lifecycle of workflow execution, including dependency analysis, execution-mode selection, and resource-aware placement. To this end, it integrates structured intra-cluster orchestration with a leader-selected, supermaster-driven inter-cluster coordination layer, determining where and how each workflow function should be executed across the federated edge clusters. We implement ClusterLess using OpenFaaS as the serverless execution substrate and Argo for workflow management, and deploy it on a realistic testbed of six edge clusters comprising 64 heterogeneous edge nodes. Experimental results with concurrent serverless workflows, spanning 18 workload configurations across different input sizes and deadline classes, show that ClusterLess reduces workflow completion time by up to 40%, increases deadline satisfaction from below 50% to over 90%, and confines deadline violations to single-digit seconds compared to four baseline methods.