OneEdge

Abstract

Resource management for geo-distributed infrastructures is challenging due to the scarcity and non-uniformity of edge resources, as well as the high client mobility and workload surges inherent to situation awareness applications. Due to their centralized nature, state-of-the-art schedulers that work well in datacenters lack the performance and feature requirements of such applications. We present OneEdge, a hybrid control plane that enables autonomous decision-making at edge sites for localized, rapid single-site application deployment. Edge sites handle mobility, churn, and load spikes, by cooperating with a centralized controller that allows coordinated multi-site scheduling and dynamic reconfiguration. OneEdge's scheduling decisions are driven by each application's end-to-end service level objective (E2E SLO) as well as the specific requirements of situation awareness applications. OneEdge's novel distributed state management combines autonomous decision-making at the edge sites for rapid localized resource allocations with decision-making at the central controller when multi-site application deployment is needed. Using a mix of applications on multi-region Azure instances, we show that, in contrast to centralized or fully distributed control planes, OneEdge caters to the unique requirements of situation awareness applications. Compared to a centralized control plane, OneEdge reduces deployment latency by 66% for single-site applications, without compromising E2E SLOs.