{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,14]],"date-time":"2026-08-14T06:31:26Z","timestamp":1786689086410,"version":"3.56.0"},"reference-count":63,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,6,19]],"date-time":"2026-06-19T00:00:00Z","timestamp":1781827200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100020473","name":"Ministry of Research Technology and Higher Education of the Republic of Indonesia","doi-asserted-by":"publisher","award":["017\/C3\/DT.05.00\/PL\/2025"],"award-info":[{"award-number":["017\/C3\/DT.05.00\/PL\/2025"]}],"id":[{"id":"10.13039\/100020473","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100020473","name":"Ministry of Research Technology and Higher Education of the Republic of Indonesia","doi-asserted-by":"publisher","award":["1237\/PKS\/ITS\/2025"],"award-info":[{"award-number":["1237\/PKS\/ITS\/2025"]}],"id":[{"id":"10.13039\/100020473","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100014823","name":"Direktorat Riset dan Pengabdian Masyarakat","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100014823","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Array"],"published-print":{"date-parts":[[2026,9]]},"DOI":"10.1016\/j.array.2026.101026","type":"journal-article","created":{"date-parts":[[2026,6,23]],"date-time":"2026-06-23T16:22:58Z","timestamp":1782231778000},"page":"101026","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["CloudX: A dual-layered cloud native architecture for GPU resource management using interactive notebook"],"prefix":"10.1016","volume":"31","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8762-3141","authenticated-orcid":false,"given":"Ary Mazharuddin","family":"Shiddiqi","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Royyana Muslim","family":"Ijtihadie","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Timothy Girry","family":"Kale","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rizky Januar","family":"Akbar","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dini Adni","family":"Navastara","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nuniek","family":"Fahriani","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gloriyano Cristho Daniel","family":"Pepuho","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Urdhanaka","family":"Aptanagi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ntivuguruzwa Jean","family":"De La Croix","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"1","key":"10.1016\/j.array.2026.101026_b1","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1186\/s13677-023-00471-1","article-title":"A survey of Kubernetes scheduling algorithms","volume":"12","author":"Senjab","year":"2023","journal-title":"J Cloud Comput"},{"issue":"3","key":"10.1016\/j.array.2026.101026_b2","doi-asserted-by":"crossref","first-page":"690","DOI":"10.32996\/jcsts.2025.7.3.79","article-title":"Scalable cloud architectures for real-time AI: Dynamic resource allocation for inference optimization","volume":"7","author":"Chennupati","year":"2025","journal-title":"J Comput Sci Technol Stud"},{"issue":"15","key":"10.1016\/j.array.2026.101026_b3","first-page":"38","article-title":"Dynamic GPU-aware scheduling for distributed data science workloads in Kubernetes","volume":"13","author":"Chaudhari","year":"2025","journal-title":"Eur J Comput Sci Inf Technol"},{"issue":"361","key":"10.1016\/j.array.2026.101026_b4","article-title":"A fine-grained GPU sharing and job scheduling for deep learning jobs on the cloud","volume":"81","author":"Chung","year":"2025","journal-title":"J Supercomput"},{"issue":"105128","key":"10.1016\/j.array.2026.101026_b5","article-title":"Leveraging Multi-Instance GPUs through moldable task scheduling","volume":"204","author":"Villarrubia","year":"2025","journal-title":"J Parallel Distrib Comput"},{"issue":"9","key":"10.1016\/j.array.2026.101026_b6","doi-asserted-by":"crossref","first-page":"2553","DOI":"10.1109\/TPDS.2023.3293835","article-title":"DeepBoot: Dynamic scheduling system for training and inference deep learning tasks in GPU cluster","volume":"34","author":"Chen","year":"2023","journal-title":"IEEE Trans Parallel Distrib Syst"},{"issue":"1","key":"10.1016\/j.array.2026.101026_b7","doi-asserted-by":"crossref","first-page":"591","DOI":"10.1007\/s11227-022-04682-2","article-title":"KubeGPU: efficient sharing and isolation mechanisms for GPU resource management in container cloud: W. Shen et al.","volume":"79","author":"Shen","year":"2023","journal-title":"J Supercomput"},{"key":"10.1016\/j.array.2026.101026_b8","series-title":"16th USENIX symposium on operating systems design and implementation","first-page":"579","article-title":"Looking beyond GPUs for DNN scheduling on Multi-Tenant clusters","author":"Mohan","year":"2022"},{"key":"10.1016\/j.array.2026.101026_b9","series-title":"2023 IEEE international conference on control, electronics and computer technology","first-page":"346","article-title":"Performance evaluation for deploying dockerized web application on AWS, GCP, and Azure","author":"Kurniawan","year":"2023"},{"key":"10.1016\/j.array.2026.101026_b10","series-title":"Proceedings - 2022 IEEE international conference on cybernetics and computational intelligence","first-page":"236","article-title":"Performance analysis of AWS and GCP cloud providers","author":"Noviani","year":"2022"},{"key":"10.1016\/j.array.2026.101026_b11","article-title":"A survey on multi-objective hyperparameter optimization algorithms for machine learning","author":"Morales-Hern\u00e1ndez","year":"2022","journal-title":"Artif Intell Rev"},{"key":"10.1016\/j.array.2026.101026_b12","series-title":"2022 IEEE 24th int conf on high performance computing & communications; 8th int conf on data science & systems; 20th int conf on smart city; 8th int conf on dependability in sensor, cloud & big data systems & application","first-page":"275","article-title":"Fine-grained scheduling for containerized HPC workloads in kubernetes clusters","author":"Liu","year":"2022"},{"issue":"1","key":"10.1016\/j.array.2026.101026_b13","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1186\/s13677-023-00471-1","article-title":"A survey of Kubernetes scheduling algorithms","volume":"12","author":"Senjab","year":"2023","journal-title":"J Cloud Comput"},{"issue":"1","key":"10.1016\/j.array.2026.101026_b14","first-page":"895","article-title":"Multi-objective task scheduling algorithm in cloud computing using improved squirrel search algorithm","volume":"17","author":"Ciptaningtyas","year":"2024","journal-title":"Int J Intell Eng Syst"},{"issue":"1","key":"10.1016\/j.array.2026.101026_b15","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1186\/s13677-023-00445-3","article-title":"Load balancing scheduling mechanism for OpenStack and Docker integration","volume":"12","author":"Qian","year":"2023","journal-title":"J Cloud Comput"},{"issue":"7","key":"10.1016\/j.array.2026.101026_b16","doi-asserted-by":"crossref","first-page":"3934","DOI":"10.1016\/j.jksuci.2021.03.002","article-title":"Container scheduling techniques: A survey and assessment","volume":"34","author":"Ahmad","year":"2022","journal-title":"J King Saud Univ \u2013 Comput Inf Sci"},{"issue":"22s","key":"10.1016\/j.array.2026.101026_b17","first-page":"1108","article-title":"Container scheduling: A taxonomy, open issues and future directions","volume":"12","author":"Prajapati","year":"2024","journal-title":"Int J Intell Syst Appl Eng (IJISAE)"},{"key":"10.1016\/j.array.2026.101026_b18","doi-asserted-by":"crossref","DOI":"10.1016\/j.jpdc.2023.104776","article-title":"Interference-aware opportunistic job placement for shared distributed deep learning clusters","volume":"183","author":"Li","year":"2024","journal-title":"J Parallel Distrib Comput"},{"issue":"11","key":"10.1016\/j.array.2026.101026_b19","doi-asserted-by":"crossref","first-page":"2781","DOI":"10.1109\/TPDS.2021.3136245","article-title":"ASTRAEA: A fair deep learning scheduler for multi-tenant GPU clusters","volume":"33","author":"Ye","year":"2022","journal-title":"IEEE Trans Parallel Distrib Syst"},{"key":"10.1016\/j.array.2026.101026_b20","doi-asserted-by":"crossref","DOI":"10.1016\/j.sysarc.2024.103138","article-title":"NGS: A network GPGPU system for orchestrating remote and virtual accelerators","volume":"151","author":"Prades","year":"2024","journal-title":"J Syst Archit"},{"key":"10.1016\/j.array.2026.101026_b21","doi-asserted-by":"crossref","first-page":"282","DOI":"10.1016\/j.future.2021.10.007","article-title":"Distributed workflows with Jupyter","volume":"128","author":"Colonnelli","year":"2022","journal-title":"Future Gener Comput Syst"},{"key":"10.1016\/j.array.2026.101026_b22","article-title":"VNF and CNF placement in 5G: Recent advances and future trends","volume":"20","author":"Attaoui","year":"2022","journal-title":"IEEE Trans Netw Serv Manag"},{"key":"10.1016\/j.array.2026.101026_b23","series-title":"2021 IEEE 41st international conference on distributed computing systems","first-page":"359","article-title":"A multi-tenant framework for cloud container services","author":"Zheng","year":"2021"},{"key":"10.1016\/j.array.2026.101026_b24","doi-asserted-by":"crossref","first-page":"32597","DOI":"10.1109\/ACCESS.2024.3369031","article-title":"A hierarchical namespace approach for multi-tenancy in distributed clouds","volume":"12","author":"Simi\u0107","year":"2024","journal-title":"IEEE Access"},{"key":"10.1016\/j.array.2026.101026_b25","series-title":"2022 22nd IEEE international symposium on cluster, cloud and internet computing","first-page":"695","article-title":"Schedtune: A heterogeneity-aware gpu scheduler for deep learning","author":"Albahar","year":"2022"},{"key":"10.1016\/j.array.2026.101026_b26","series-title":"2023 IEEE 43rd international conference on distributed computing systems","first-page":"898","article-title":"TailGuard: Tail latency SLO guaranteed task scheduling for data-intensive user-facing applications","author":"Wang","year":"2023"},{"key":"10.1016\/j.array.2026.101026_b27","series-title":"15th {USENIX} symposium on operating systems design and implementation","article-title":"Pollux: Co-adaptive cluster scheduling for goodput-optimized deep learning","author":"Qiao","year":"2021"},{"key":"10.1016\/j.array.2026.101026_b28","series-title":"Proceedings of IEEE international symposium on high-performance computer architecture","article-title":"MoCA: Memory-centric, adaptive execution for multi-tenant deep neural networks","author":"Kim","year":"2023"},{"key":"10.1016\/j.array.2026.101026_b29","article-title":"Cost-efficient and scalable GPU scheduling strategies in multi-tenant cloud environments for AI workloads","author":"Kathiresan","year":"2025","journal-title":"Int J Comput Sci Inf Technol Res (IJCSITR)"},{"key":"10.1016\/j.array.2026.101026_b30","series-title":"Improving GPU multi-tenancy through dynamic multi-instance GPU reconfiguration","author":"Wang","year":"2024"},{"key":"10.1016\/j.array.2026.101026_b31","series-title":"Proceedings of the fifteenth European conference on computer systems","first-page":"1","article-title":"Balancing efficiency and fairness in heterogeneous GPU clusters for deep learning","author":"Chaudhary","year":"2020"},{"key":"10.1016\/j.array.2026.101026_b32","series-title":"Proceedings of the 11th ACM symposium on cloud computing","first-page":"492","article-title":"Gslice: controlled spatial sharing of gpus for a scalable inference platform","author":"Dhakal","year":"2020"},{"issue":"3","key":"10.1016\/j.array.2026.101026_b33","doi-asserted-by":"crossref","first-page":"391","DOI":"10.1109\/TPDS.2024.3522333","article-title":"Integrated and fungible scheduling of deep learning workloads using multi-agent reinforcement learning","volume":"36","author":"Li","year":"2025","journal-title":"IEEE Trans Parallel Distrib Syst"},{"key":"10.1016\/j.array.2026.101026_b34","series-title":"Proceedings of the 25th international middleware conference","first-page":"36","article-title":"Optimal resource efficiency with fairness in heterogeneous GPU clusters","author":"Mo","year":"2024"},{"key":"10.1016\/j.array.2026.101026_b35","series-title":"Proceedings - 2017 IEEE international conference on computational science and engineering and IEEE\/IFIP international conference on embedded and ubiquitous computing","first-page":"230","article-title":"VMR: Virtual machine replacement algorithm for QoS and energy-awareness in cloud data centers","volume":"Vol. 2","author":"Ali","year":"2017"},{"issue":"4","key":"10.1016\/j.array.2026.101026_b36","doi-asserted-by":"crossref","first-page":"1367","DOI":"10.1007\/s11277-018-6089-3","article-title":"An energy-efficient dynamic resource management approach based on clustering and meta-heuristic algorithms in cloud computing IaaS platforms: Energy efficient dynamic cloud resource management","volume":"104","author":"Askarizade Haghighi","year":"2019","journal-title":"Wirel Pers Commun"},{"issue":"2","key":"10.1016\/j.array.2026.101026_b37","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1007\/s11235-022-00893-3","article-title":"Quality enhancement in a mm-wave multi-hop, multi-tier heterogeneous 5G network architecture","volume":"80","author":"Ahmed","year":"2022","journal-title":"Telecommun Syst"},{"key":"10.1016\/j.array.2026.101026_b38","series-title":"2021 international conference on computer communications and networks","first-page":"1","article-title":"Mck8s: An orchestration platform for geo-distributed multi-cluster environments","author":"Tamiru","year":"2021"},{"key":"10.1016\/j.array.2026.101026_b39","series-title":"Proceeding of 2011 IEEE third international conference on cloud computing technology and science","article-title":"ViteraaS: Virtual tenants environment as a Service","author":"Doelitzscher","year":"2021"},{"key":"10.1016\/j.array.2026.101026_b40","series-title":"International conference on high performance computing","first-page":"347","article-title":"Virtual clusters: isolated, containerized HPC environments in kubernetes","author":"Zervas","year":"2022"},{"key":"10.1016\/j.array.2026.101026_b41","series-title":"2018 IEEE 8th annual computing and communication workshop and conference","first-page":"341","article-title":"Edge network model based on double dimension","volume":"Vol. 2018-January","author":"Yin","year":"2018"},{"issue":"2","key":"10.1016\/j.array.2026.101026_b42","doi-asserted-by":"crossref","first-page":"5595","DOI":"10.1109\/TCE.2025.3571035","article-title":"Attention-driven graph convolutional networks for deadline-constrained virtual machine task allocation in edge computing","volume":"71","author":"Ali","year":"2025","journal-title":"IEEE Trans Consum Electron"},{"key":"10.1016\/j.array.2026.101026_b43","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2025.127763","article-title":"Resilience to deception attacks in consensus tracking control of incommensurate fractional-order power systems via adaptive RBF neural network","volume":"283","author":"Sharafian","year":"2025","journal-title":"Expert Syst Appl"},{"key":"10.1016\/j.array.2026.101026_b44","series-title":"2019 IEEE international conference on cluster computing","first-page":"1","article-title":"Kube-knots: Resource harvesting through dynamic container orchestration in GPU-based datacenters","author":"Thinakaran","year":"2019"},{"issue":"3","key":"10.1016\/j.array.2026.101026_b45","doi-asserted-by":"crossref","first-page":"3153","DOI":"10.1109\/TCC.2023.3264242","article-title":"Dynamic GPU scheduling with multi-resource awareness and live migration support","volume":"11","author":"Wang","year":"2023","journal-title":"IEEE Trans Cloud Comput"},{"key":"10.1016\/j.array.2026.101026_b46","series-title":"8th USENIX symposium on networked systems design and implementation","article-title":"Dominant resource fairness: Fair allocation of multiple resource types","author":"Ghodsi","year":"2011"},{"key":"10.1016\/j.array.2026.101026_b47","doi-asserted-by":"crossref","DOI":"10.1287\/moor.2024.0714","article-title":"Fair and efficient multi-resource allocation for cloud computing: Beyond dominant resource fairness","author":"Bei","year":"2026","journal-title":"Math Oper Res"},{"key":"10.1016\/j.array.2026.101026_b48","series-title":"Proc. 53rd international conference on parallel processing","first-page":"504","article-title":"MIGER: Integrating multi-instance GPU and multi-process service for deep learning clusters","author":"Zhang","year":"2024"},{"issue":"7","key":"10.1016\/j.array.2026.101026_b49","doi-asserted-by":"crossref","DOI":"10.1145\/3539606","article-title":"Kubernetes scheduling: Taxonomy, ongoing issues and challenges","volume":"55","author":"Carri\u00f3n","year":"2022","journal-title":"ACM Comput Surv"},{"issue":"1","key":"10.1016\/j.array.2026.101026_b50","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1186\/s13677-020-00194-7","article-title":"Cloud resource orchestration in the multi-cloud landscape: A systematic review of existing frameworks","volume":"9","author":"Tomarchio","year":"2020","journal-title":"J Cloud Comput"},{"issue":"1","key":"10.1016\/j.array.2026.101026_b51","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1186\/s13677-023-00516-5","article-title":"Orchestration in the cloud-to-things compute continuum: Taxonomy, survey and future directions","volume":"12","author":"Ullah","year":"2023","journal-title":"J Cloud Comput"},{"issue":"1","key":"10.1016\/j.array.2026.101026_b52","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":"10.1016\/j.array.2026.101026_b53","series-title":"Presentation at CS3 2024 \u2013 Cloud storage synchronization and sharing","article-title":"JupyterHub on Kubernetes as a platform for developing secure shared environment for data analysis at MAX IV","author":"Salnikov","year":"2024"},{"key":"10.1016\/j.array.2026.101026_b54","series-title":"IEEE\/ACM HPC for urgent decision making","article-title":"Towards interactive, reproducible analytics at scale on HPC systems","author":"Cholia","year":"2020"},{"issue":"1","key":"10.1016\/j.array.2026.101026_b55","first-page":"36","article-title":"Improving YOLO object detection performance on single-board computer using virtual machine","volume":"5","author":"Haq","year":"2024","journal-title":"Emerg Inf Sci Technol"},{"key":"10.1016\/j.array.2026.101026_b56","series-title":"Jupyter enterprise gateway: A lightweight, multi-tenant, scalable and secure gateway that enables Jupyter notebooks to share resources across distributed clusters","author":"Jupyter Enterprise Gateway Contributors","year":"2024"},{"key":"10.1016\/j.array.2026.101026_b57","series-title":"Proceedings of the 2023 ACM\/SPEC international conference on performance engineering","article-title":"Lightweight Kubernetes distributions: A performance comparison of MicroK8s, k3s, k0s, and Microshift","author":"Koziolek","year":"2023"},{"key":"10.1016\/j.array.2026.101026_b58","series-title":"JupyterHub documentation","author":"Project Jupyter","year":"2025"},{"issue":"2","key":"10.1016\/j.array.2026.101026_b59","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1109\/MM.2020.2974843","article-title":"MLPerf: An industry standard benchmark suite for machine learning performance","volume":"40","author":"Mattson","year":"2020","journal-title":"IEEE Micro"},{"key":"10.1016\/j.array.2026.101026_b60","series-title":"2020 IEEE international symposium on performance analysis of systems and software","first-page":"24","article-title":"Demystifying the mlperf training benchmark suite","author":"Verma","year":"2020"},{"key":"10.1016\/j.array.2026.101026_b61","series-title":"Proceedings of the 2019 conference of the North American chapter of the association for computational linguistics: human language technologies, volume 1 (long and short papers)","first-page":"4171","article-title":"BERT: Pre-training of deep bidirectional transformers for language understanding","author":"Devlin","year":"2019"},{"key":"10.1016\/j.array.2026.101026_b62","series-title":"2020 ACM\/IEEE 47th annual international symposium on computer architecture","first-page":"446","article-title":"Mlperf inference benchmark","author":"Reddi","year":"2020"},{"key":"10.1016\/j.array.2026.101026_b63","series-title":"Synergy: Resource sensitive DNN scheduling in multi-tenant clusters","author":"Mohan","year":"2022"}],"container-title":["Array"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2590005626003498?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2590005626003498?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,8,14]],"date-time":"2026-08-14T06:07:50Z","timestamp":1786687670000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S2590005626003498"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9]]},"references-count":63,"alternative-id":["S2590005626003498"],"URL":"https:\/\/doi.org\/10.1016\/j.array.2026.101026","relation":{},"ISSN":["2590-0056"],"issn-type":[{"value":"2590-0056","type":"print"}],"subject":[],"published":{"date-parts":[[2026,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"CloudX: A dual-layered cloud native architecture for GPU resource management using interactive notebook","name":"articletitle","label":"Article Title"},{"value":"Array","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.array.2026.101026","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 The Authors. Published by Elsevier Inc.","name":"copyright","label":"Copyright"}],"article-number":"101026"}}