Optimizing Kubernetes Deployment of Robotic Applications with HEFT-based Container Orchestration

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.

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Publication Details

Published
2024-10-14
DOI
https://doi.org/10.1109/iros58592.2024.10802072
Primary Topic
Distributed and Parallel Computing Systems
Type
article
Field-Weighted Citation Impact
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article

Optimizing Kubernetes Deployment of Robotic Applications with HEFT-based Container Orchestration

Francesco Lumpp, Franco Fummi, Nicola Bombieri
Distributed and Parallel Computing Systems
article

Optimizing Kubernetes Deployment of Robotic Applications with HEFT-based Container Orchestration

Francesco Lumpp, Franco Fummi, Nicola Bombieri
article en

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.

University of Verona (IT)
Openalex Percentile: Top 72%
Distributed and Parallel Computing Systems
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