FaasOrc: A bi-level function scheduling and caching framework for serverless edge computing
Year: 2026
Type: article
Abstract: Serverless computing, underpinned by an event-driven approach with transient stateless containers, significantly enhances resource efficiency and simplifies function development. To maintain an acceptable Quality of Service (QoS) agreed in the Service Level Agreement (SLA), service providers need to improve the response latency while considering resource efficiency. However, cold-start delays in container initialization often lead to considerable latency in these applications. Existing mitigation strategies, such as pre-warming and function caching, are inadequate due to workload skewness and oscillation across edge nodes. These limitations are particularly critical in resource-constrained edge environments. We must jointly consider multiple factors, such as node status, function resource requirement and function popularity. To overcome these limitations, this paper presents FaasOrc , a bi-level function orchestration framework to mitigate workload skewness and oscillation across edge nodes. FaasOrc uses a cluster-level scheduler to schedule requests and a node-level manager to detect popular functions. Our comprehensive evaluation, consisting of two parts: simulations and a real-system prototype over Knative , benchmarks the proposed solution against existing scheduling and caching strategies. The findings highlight our method’s capability to reduce the response latency by 31.4%.
Authors: Chen Chen, Lars Nagel, Lin Cui, Weijia Jia, Fung Po Tso
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,120
Award: G6691695239
OpenAlex ID: W7155602672