This study addresses the challenge of deploying robotic software with Quality of Service (QoS) constraints in Edge-Cloud computing clusters. The paper introduces HEFT4K, an event-driven scheduling method tailored for Kubernetes-managed systems based on the Heterogeneous Early Finish Time (HEFT) algorithm. This algorithm reduces software execution time (makespan) and facilitates re-mapping in case of node failures, involving only essential containers to maintain uninterrupted robot functionality. Experimental results, conducted on a real-world robot and synthetic benchmarks, show a 75% speedup in makespan compared to the standard Kubernetes scheduler, enhancing the efficiency of QoS-focused scheduling for robotic applications in distributed systems.
Optimizing Kubernetes Deployment of Robotic Applications with HEFT-based Container Orchestration
Francesco Lumpp;Franco Fummi;Nicola Bombieri
2024-01-01
Abstract
This study addresses the challenge of deploying robotic software with Quality of Service (QoS) constraints in Edge-Cloud computing clusters. The paper introduces HEFT4K, an event-driven scheduling method tailored for Kubernetes-managed systems based on the Heterogeneous Early Finish Time (HEFT) algorithm. This algorithm reduces software execution time (makespan) and facilitates re-mapping in case of node failures, involving only essential containers to maintain uninterrupted robot functionality. Experimental results, conducted on a real-world robot and synthetic benchmarks, show a 75% speedup in makespan compared to the standard Kubernetes scheduler, enhancing the efficiency of QoS-focused scheduling for robotic applications in distributed systems.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.