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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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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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. |
format | Online Article Text |
id | pubmed-9030099 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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