Beyond Trade-Offs: Mashing Serverful and Serverless Cloud Resources for Budget-Constrained Workflow Execution

Abstract

Serverless computing is characterized by finegrained billing and elastic scalability, which makes it highly suitable for workflow execution. Nevertheless, it is hindered by cold-start latency and rigid execution constraints. In comparison, conventional serverful cloud resources like virtual machines employ coarser-grained provisioning but offer lower unit computing costs. This paper explores the combination of serverful and serverless resources to leverage their complementary advantages for efficient and cost-effective workflow execution. We design a hybrid resource management framework that dynamically assigns workflow tasks across these two resource types. Furthermore, we present a Budget-constrained Workflow scheduling algorithm for Blended cloud environments (BWB), which aims to minimize makespan under user-defined budget constraints. Experiments are performed using realistic workflow applications in real-world cloud scenarios. By comparing BWB with state-of-the-art serverful, serverless, and hybrid scheduling methods, the results show that BWB reduces the average makespan by at least 16.9%, which effectively validates the cost-effectiveness of the blended cloud resource scheme for workflow execution.