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Load-Balancing of Kubernetes-Based Edge Computing Infrastructure Using Resource Adaptive Proxy

Kubernetes (K8s) is expected to be a key container orchestration tool for edge computing infrastructures owing to its various features for supporting container deployment and dynamic resource management. For example, its horizontal pod autoscaling feature provides service availability and scalabilit...

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Autores principales: Nguyen, Quang-Minh, Phan, Linh-An, Kim, Taehong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9030099/
https://www.ncbi.nlm.nih.gov/pubmed/35458853
http://dx.doi.org/10.3390/s22082869
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author Nguyen, Quang-Minh
Phan, Linh-An
Kim, Taehong
author_facet Nguyen, Quang-Minh
Phan, Linh-An
Kim, Taehong
author_sort Nguyen, Quang-Minh
collection PubMed
description Kubernetes (K8s) is expected to be a key container orchestration tool for edge computing infrastructures owing to its various features for supporting container deployment and dynamic resource management. For example, its horizontal pod autoscaling feature provides service availability and scalability by increasing the number of replicas. kube-proxy provides traffic load-balancing between replicas by distributing client requests equally to all pods (replicas) of an application in a K8s cluster. However, this approach can result in long delays when requests are forwarded to remote workers, especially in edge computing environments where worker nodes are geographically dispersed. Moreover, if the receiving worker is overloaded, the request-processing delay can increase significantly. To overcome these limitations, this paper proposes an enhanced load balancer called resource adaptive proxy (RAP). RAP periodically monitors the resource status of each pod and the network status among worker nodes to aid in load-balancing decisions. Furthermore, it preferentially handles requests locally to the maximum extent possible. If the local worker node is overloaded, RAP forwards its requests to the best node in the cluster while considering resource availability. Our experimental results demonstrated that RAP could significantly improve throughput and reduce request latency compared with the default load-balancing mechanism of K8s.
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spelling pubmed-90300992022-04-23 Load-Balancing of Kubernetes-Based Edge Computing Infrastructure Using Resource Adaptive Proxy Nguyen, Quang-Minh Phan, Linh-An Kim, Taehong Sensors (Basel) Article Kubernetes (K8s) is expected to be a key container orchestration tool for edge computing infrastructures owing to its various features for supporting container deployment and dynamic resource management. For example, its horizontal pod autoscaling feature provides service availability and scalability by increasing the number of replicas. kube-proxy provides traffic load-balancing between replicas by distributing client requests equally to all pods (replicas) of an application in a K8s cluster. However, this approach can result in long delays when requests are forwarded to remote workers, especially in edge computing environments where worker nodes are geographically dispersed. Moreover, if the receiving worker is overloaded, the request-processing delay can increase significantly. To overcome these limitations, this paper proposes an enhanced load balancer called resource adaptive proxy (RAP). RAP periodically monitors the resource status of each pod and the network status among worker nodes to aid in load-balancing decisions. Furthermore, it preferentially handles requests locally to the maximum extent possible. If the local worker node is overloaded, RAP forwards its requests to the best node in the cluster while considering resource availability. Our experimental results demonstrated that RAP could significantly improve throughput and reduce request latency compared with the default load-balancing mechanism of K8s. MDPI 2022-04-08 /pmc/articles/PMC9030099/ /pubmed/35458853 http://dx.doi.org/10.3390/s22082869 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Nguyen, Quang-Minh
Phan, Linh-An
Kim, Taehong
Load-Balancing of Kubernetes-Based Edge Computing Infrastructure Using Resource Adaptive Proxy
title Load-Balancing of Kubernetes-Based Edge Computing Infrastructure Using Resource Adaptive Proxy
title_full Load-Balancing of Kubernetes-Based Edge Computing Infrastructure Using Resource Adaptive Proxy
title_fullStr Load-Balancing of Kubernetes-Based Edge Computing Infrastructure Using Resource Adaptive Proxy
title_full_unstemmed Load-Balancing of Kubernetes-Based Edge Computing Infrastructure Using Resource Adaptive Proxy
title_short Load-Balancing of Kubernetes-Based Edge Computing Infrastructure Using Resource Adaptive Proxy
title_sort load-balancing of kubernetes-based edge computing infrastructure using resource adaptive proxy
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9030099/
https://www.ncbi.nlm.nih.gov/pubmed/35458853
http://dx.doi.org/10.3390/s22082869
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