{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T22:33:20Z","timestamp":1777415600760,"version":"3.51.4"},"reference-count":39,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2022,4,8]],"date-time":"2022-04-08T00:00:00Z","timestamp":1649376000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea","doi-asserted-by":"publisher","award":["2021R1F1A1060328"],"award-info":[{"award-number":["2021R1F1A1060328"]}],"id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>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.<\/jats:p>","DOI":"10.3390\/s22082869","type":"journal-article","created":{"date-parts":[[2022,4,9]],"date-time":"2022-04-09T05:13:08Z","timestamp":1649481188000},"page":"2869","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":43,"title":["Load-Balancing of Kubernetes-Based Edge Computing Infrastructure Using Resource Adaptive Proxy"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8525-4768","authenticated-orcid":false,"given":"Quang-Minh","family":"Nguyen","sequence":"first","affiliation":[{"name":"School of Information and Communication Engineering, Chungbuk National University, Cheongju 28644, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9155-9819","authenticated-orcid":false,"given":"Linh-An","family":"Phan","sequence":"additional","affiliation":[{"name":"School of Information and Communication Engineering, Chungbuk National University, Cheongju 28644, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6246-6218","authenticated-orcid":false,"given":"Taehong","family":"Kim","sequence":"additional","affiliation":[{"name":"School of Information and Communication Engineering, Chungbuk National University, Cheongju 28644, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,4,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"439","DOI":"10.1109\/JIOT.2017.2767608","article-title":"Future Edge Cloud and Edge Computing for Internet of Things Applications","volume":"5","author":"Pan","year":"2017","journal-title":"IEEE Internet Things J."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"11526","DOI":"10.1109\/JIOT.2021.3052498","article-title":"IoT Service Slicing and Task Offloading for Edge Computing","volume":"8","author":"Hwang","year":"2021","journal-title":"IEEE Internet Things J."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Felter, W., Ferreira, A., Rajamony, R., and Rubio, J. (2015, January 29\u201331). An updated performance comparison of virtual machines and linux containers. Proceedings of the 2015 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS), Philadelphia, PA, USA.","DOI":"10.1109\/ISPASS.2015.7095802"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"3107","DOI":"10.1109\/TWC.2020.3047496","article-title":"Edge Computing Resource Allocation for Unmanned Aerial Vehicle Assisted Mobile Network With Blockchain Applications","volume":"20","author":"Xu","year":"2021","journal-title":"IEEE Trans. Wirel. Commun."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Bonomi, F., Milito, R., Zhu, J., and Addepalli, S. (2012, January 17). Fog Computing and Its Role in the Internet of Things. Proceedings of the First Edition of the MCC Workshop on Mobile Cloud Computing, MCC \u201912, Helsinki, Finland.","DOI":"10.1145\/2342509.2342513"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1186\/s13677-021-00231-z","article-title":"Container orchestration on HPC systems through Kubernetes","volume":"10","author":"Zhou","year":"2021","journal-title":"J. Cloud Comput."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1109\/MCC.2015.51","article-title":"Containerization and the PaaS Cloud","volume":"2","author":"Pahl","year":"2015","journal-title":"J. Cloud Comput."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"8133","DOI":"10.1109\/JIOT.2020.3042502","article-title":"Docker-Based Intelligent Fall Detection Using Edge-Fog Cloud Infrastructure","volume":"8","author":"Divya","year":"2020","journal-title":"IEEE Internet Things J."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1109\/MCC.2017.4250933","article-title":"Key Characteristics of a Container Orchestration Platform to Enable a Modern Application","volume":"4","author":"Khan","year":"2017","journal-title":"IEEE Cloud Comput."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"4228","DOI":"10.1109\/JIOT.2019.2939534","article-title":"KEIDS: Kubernetes-Based Energy and Interference Driven Scheduler for Industrial IoT in Edge-Cloud Ecosystem","volume":"7","author":"Kaur","year":"2020","journal-title":"IEEE Internet Things J."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"635","DOI":"10.1109\/TCC.2018.2794344","article-title":"Locality-aware scheduling for containers in cloud computing","volume":"8","author":"Zhao","year":"2018","journal-title":"IEEE Trans. Cloud Comput."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"4712","DOI":"10.1109\/TII.2018.2851241","article-title":"Tasks scheduling and resource allocation in fog computing based on containers for smart manufacturing","volume":"14","author":"Yin","year":"2018","journal-title":"IEEE Trans. Ind. Inform."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1109\/MCOM.001.1900660","article-title":"Toward Highly Scalable Load Balancing in Kubernetes Clusters","volume":"58","author":"Nguyen","year":"2020","journal-title":"IEEE Commun. Mag."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"150936","DOI":"10.1109\/ACCESS.2019.2947652","article-title":"Foundations and Evolution of Modern Computing Paradigms: Cloud, IoT, Edge, and Fog","volume":"7","author":"Tange","year":"2019","journal-title":"IEEE Access"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"2359","DOI":"10.1109\/COMST.2017.2717482","article-title":"How Can Edge Computing Benefit From Software-Defined Networking: A Survey, Use Cases, and Future Directions","volume":"19","author":"Baktir","year":"2017","journal-title":"IEEE Commun. Surv. Tutor."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"11088","DOI":"10.1109\/JIOT.2021.3052082","article-title":"Resource Provisioning in Edge Computing for Latency-Sensitive Applications","volume":"8","author":"Abouaomar","year":"2021","journal-title":"IEEE Internet Things J."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"486","DOI":"10.1016\/j.future.2020.12.021","article-title":"Dynamic fog-to-fog offloading in SDN-based fog computing systems","volume":"117","author":"Phan","year":"2021","journal-title":"Future Gener. Comput. Syst."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Nguyen, T.T., Yeom, Y.J., Kim, T., Park, D.H., and Kim, S. (2020). Horizontal Pod Autoscaling in Kubernetes for Elastic Container Orchestration. Sensors, 20.","DOI":"10.3390\/s20164621"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Kayal, P. (2020, January 2\u201316). Kubernetes in Fog Computing: Feasibility Demonstration, Limitations and Improvement Scope: Invited Paper. Proceedings of the 2020 IEEE 6th World Forum on Internet of Things (WF-IoT), New Orleans, LA, USA.","DOI":"10.1109\/WF-IoT48130.2020.9221340"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Santos, J., Wauters, T., Volckaert, B., and De Turck, F. (2020, January 20\u201324). Towards delay-aware container-based Service Function Chaining in Fog Computing. Proceedings of the NOMS 2020\u20142020 IEEE\/IFIP Network Operations and Management Symposium, Budapest, Hungary.","DOI":"10.1109\/NOMS47738.2020.9110376"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1007\/s10723-021-09573-z","article-title":"Ultra-Reliable and Low-Latency Computing in the Edge with Kubernetes","volume":"19","author":"Toka","year":"2021","journal-title":"J. Grid Comput."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Wojciechowski, \u0141., Opasiak, K., Latusek, J., Wereski, M., Morales, V., Kim, T., and Hong, M. (2021, January 10\u201313). NetMARKS: Network Metrics-AwaRe Kubernetes Scheduler Powered by Service Mesh. Proceedings of the IEEE INFOCOM 2021\u2014IEEE Conference on Computer Communications, Vancouver, BC, Canada.","DOI":"10.1109\/INFOCOM42981.2021.9488670"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"183879","DOI":"10.1109\/ACCESS.2020.3029583","article-title":"ElasticFog: Elastic Resource Provisioning in Container-Based Fog Computing","volume":"8","author":"Nguyen","year":"2020","journal-title":"IEEE Access"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"18966","DOI":"10.1109\/ACCESS.2022.3150867","article-title":"Traffic-Aware Horizontal Pod Autoscaler in Kubernetes-Based Edge Computing Infrastructure","volume":"10","author":"Phuc","year":"2022","journal-title":"IEEE Access"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1016\/j.comcom.2020.04.061","article-title":"Geo-distributed efficient deployment of containers with Kubernetes","volume":"159","author":"Rossi","year":"2020","journal-title":"Comput. Commun."},{"key":"ref_26","unstructured":"Kubernetes (2022, February 16). Kubernetes Components. Available online: https:\/\/kubernetes.io\/."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Caminero, A.C., and Mu\u00f1oz-Mansilla, R. (2021). Quality of Service Provision in Fog Computing: Network-Aware Scheduling of Containers. Sensors, 21.","DOI":"10.3390\/s21123978"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1016\/j.sysarc.2016.12.007","article-title":"State machine replication in containers managed by Kubernetes","volume":"73","author":"Netto","year":"2017","journal-title":"J. Syst. Archit."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Nguyen, N.D., and Kim, T. (2021). Balanced Leader Distribution Algorithm in Kubernetes Clusters. Sensors, 21.","DOI":"10.3390\/s21030869"},{"key":"ref_30","unstructured":"Kubernetes (2022, February 16). Kubernetes Service. Available online: https:\/\/kubernetes.io\/."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Santos, J., Wauters, T., Volckaert, B., and De Turck, F. (2019, January 24\u201328). Towards Network-Aware Resource Provisioning in Kubernetes for Fog Computing Applications. Proceedings of the 2019 IEEE Conference on Network Softwarization (NetSoft), Paris, France.","DOI":"10.1109\/NETSOFT.2019.8806671"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Hong, C.H., Lee, K., Kang, M., and Yoo, C. (2018). qCon: QoS-Aware network resource management for fog computing. Sensors, 18.","DOI":"10.3390\/s18103444"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"5031","DOI":"10.1109\/TVT.2019.2904244","article-title":"Collaborative Cloud and Edge Computing for Latency Minimization","volume":"68","author":"Ren","year":"2019","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1109\/MCOM.2016.1600492CM","article-title":"EdgeIoT: Mobile Edge Computing for the Internet of Things","volume":"54","author":"Sun","year":"2016","journal-title":"IEEE Commun. Mag."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"104874","DOI":"10.1109\/ACCESS.2021.3099531","article-title":"An Intelligent IoT Approach for Analyzing and Managing Crowds","volume":"9","author":"Alenazi","year":"2021","journal-title":"IEEE Access"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"13775","DOI":"10.1109\/ACCESS.2021.3052458","article-title":"Improving IoT Services Using a Hybrid Fog-Cloud Offloading","volume":"9","author":"Aljanabi","year":"2021","journal-title":"IEEE Access"},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Eidenbenz, R., Pignolet, Y.A., and Ryser, A. (2020, January 20\u201323). Latency-Aware Industrial Fog Application Orchestration with Kubernetes. Proceedings of the 2020 Fifth International Conference on Fog and Mobile Edge Computing (FMEC), Paris, France.","DOI":"10.1109\/FMEC49853.2020.9144934"},{"key":"ref_38","unstructured":"(2022, February 16). Kubernetes Metrics Server. Available online: https:\/\/github.com\/kubernetes-sigs\/metrics-server."},{"key":"ref_39","unstructured":"(2022, February 16). Apache HTTP Server Benchmarking Tool. Available online: https:\/\/httpd.apache.org\/."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/8\/2869\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T22:50:27Z","timestamp":1760136627000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/8\/2869"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,4,8]]},"references-count":39,"journal-issue":{"issue":"8","published-online":{"date-parts":[[2022,4]]}},"alternative-id":["s22082869"],"URL":"https:\/\/doi.org\/10.3390\/s22082869","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,4,8]]}}}