Cloud-Based Scheduling Mechanism for Scalable and Resource-Efficient Centralized Controllers
Year: 2024
Type: conference-paper
Abstract: This paper proposes a novel approach to address the challenges of deploying complex robotic software in large-scale systems, i.e., Centralized Nonlinear Model Predictive Controllers (CNMPCs) for multi-agent systems. The proposed approach is based on a Kubernetes-based scheduling mechanism designed to monitor and optimize the operation of CNMPCs, while addressing the scalability limitation of centralized control schemes. By leveraging a cluster in a real-time cloud environment, the proposed mechanism effectively offloads the computational burden of CNMPCs. Through experiments, we have demonstrated the effectiveness and performance of our system, especially in scenarios where the number of robots is subject to change. Our work contributes to the advancement of cloud-based control strategies and lays the foundation for enhanced performance in cloud-controlled robotic systems.
Institution: Luleå University of Technology
Language: English
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4408281955