tinyKube: A Middleware for Dynamic Resource Management in Cloud-Edge Platforms for Large-Scale Cloud Robotics

• Published in: IEEE/IFIP Network Operations and Management Symposium pp. 1 - 8
• Main Authors: Nguyen, Chanh, Seo, Eunil, Zahid, Muhammad, Larsson, Oliver, Pokorny, Florian T., Elmroth, Erik
• Format: Conference Proceeding
• Language: English
• Published: IEEE 12.05.2025
• Subjects: Cloud Robotics; Cloud-Edge Infrastructure; Computer Science; datalogi; Dispatching; Dynamic Orchestration; Dynamic scheduling; Middleware; Monitoring; Performance Monitoring; Processor scheduling; Quality of service; Resource management; Robots; Testing
• ISBN: 9798331531645; 9798331531638
• ISSN: 2374-9709
• DOI: 10.1109/NOMS57970.2025.11073596

With the rise of ubiquitous networking and distributed computing, integrating robots with cloud-edge infrastructures offers significant potential. However, challenges remain in resource allocation and scheduling across distributed environments to meet robotics applications' performance demands. This paper introduces tinyKube, a middleware tailored for dynamic resource management across the cloud-edge platform for large-scale cloud robotics deployments. Leveraging Kubernetes for orchestration and Prometheus for monitoring, tinyKube enables unified monitoring, task dispatching, and resource provisioning across cloud-edge infrastructures. We evaluate tinyKube using a robotic gripper application on the CloudGripper testbed in a real-world cloud-edge setup. Results demonstrate its ability to automate task dispatching and resource allocation, dynamically adapting to QoS requirements and workload variations. By simplifying resource management, tinyKube accelerates the development, testing, and deployment of large-scale cloud robotics applications, facilitating more efficient real-world implementation.