Skip to main content
Log in

Containerization technologies: taxonomies, applications and challenges

  • Published:
The Journal of Supercomputing Aims and scope Submit manuscript

Abstract

Modern scientific research challenges require new technologies, integrated tools, reusable and complex experiments in distributed computing infrastructures. But above all, computing power for efficient data processing and analyzing. Containers technologies have emerged as a new paradigm to address such intensive scientific applications problems. Their easy deployment in a reasonable amount of time and the few required computational resource make them more suitable. Containers are considered light virtualization solutions. They enable performance isolation and flexible deployment of complex, parallel, and high-performance systems. Moreover, they gained popularity to modernize and migrate scientific applications in computing infrastructure management. Additionally, they reduce computational time processing. In this paper, we first give an overview of virtualization and containerization technologies. We discuss the taxonomies of containerization technologies of the literature, and then we provide a new one that covers and completes those proposed in the literature. We identify the most important application domains of containerization and their technological progress. Furthermore, we discuss the performance metrics used in most containerization techniques. Finally, we point out research gaps in the related aspects of containerization technology that require more research.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  1. Bermejo B, Juiz C, Guerrero C (2019) Virtualization and consolidation: a systematic review of the past 10 years of research on energy and performance. J Supercomput 75(2):808–836

    Article  Google Scholar 

  2. Menouer T, Darmon P (2019) Containers scheduling consolidation approach for cloud computing. In: Esposito C, Hong J, Choo KK. (eds) Pervasive Systems, Algorithms and Networks. I-SPAN. Communications in Computer and Information Science, vol. 1080

  3. Zheng L, et al. (2017) Performance overhead comparison between hypervisor and container based virtualization, IEEE 31st International Conference on Advanced Information Networking and Applications (AINA) pp. 955–962

  4. Chae M, Lee H, Lee K (2019) A performance comparison of linux containers and virtual machines using Docker and KVM. Cluster Comput 22:1765–1775. https://doi.org/10.1007/s10586-017-1511-2

    Article  Google Scholar 

  5. Yu B, Tian J, Ma S, Yi S, Yu D (2011) Gird or cloud? Survey on scientific computing infrastructure, IEEE International Conference on Cloud Computing and Intelligence Systems, Beijing, pp. 244–249

  6. Zhang Q, Liu L, Pu C, Dou Q, Wu L, Zhou W (2018) A comparative study of containers and virtual machines in big data environment. In: 2018 IEEE 11th International Conference on Cloud Computing (CLOUD). San Francisco, CA, pp 178–185. https://doi.org/10.1109/CLOUD.2018.00030

  7. Linux containers LXC, [Online] available March 2020: https://linuxcontainers.org/

  8. Eric Chiang Containers from Scratch. [Online], available March 2020: https://ericchiang.github.io/post/containers-from-scratch/#container-file-system

  9. Campeanu G (2018) A mapping study on microservice architectures of Internet of Things and cloud computing solutions, 2018 7th Mediterranean Conference on Embedded Computing (MECO), Budva, pp. 1–4, doi: https://doi.org/10.1109/MECO.2018.8406008

  10. OpenVZlinu containers, [online] available April 2020: http://openvz.org/

  11. Docker, [Online] available April 2020: https://docs.docker.com

  12. Singularity, [Online], available April 2020: https://www.sylabs.io/docs/

  13. uDocker. [Online], available April 2020: https://github.com/indigo-dc/udocker

  14. Beltre AM, Saha P, Govindaraju M, Younge A, Grant RE (2019) Enabling HPC workloads on cloud infrastructure using kubernetes container orchestration mechanisms. Paper presented at 2019 IEEE/ACM International Workshop on Containers and New Orchestration Paradigms forIsolated Environments in HPC(CANOPIE-HPC), Denver, CO, USA, 2019, pp. 11-20. doi: https://doi.org/10.1109/CANOPIE-HPC49598.2019.00007

  15. The apache software foundation. Mesos, apache. [Online], available April 2020: http://mesos.apache.org/

  16. Kubernetes, [online], available July 2020 : https://kubernetes.io/

  17. RedHat Openshift.[Online], available April 2020: https://www.redhat.com/en/technologies/cloud-computing/openshift

  18. Pahl C, Brogi A, Soldani J, Jamshidi P (2019) Cloud container technologies: a state-of-the-art review," in IEEE Transactions on Cloud Computing, 1 July–Sept. 2019, vol. 7, no. 3, pp. 677–692

  19. Azab A (2017) Enabling docker containers for high-performance and many-task computing," IEEE International Conference on Cloud Engineering (IC2E), Vancouver, BC , pp. 279–285, doi: https://doi.org/10.1109/IC2E.2017.52

  20. Lingayat A Badre RR, A. K. Gupta AK (2018) Integration of linux containers in openstack: an introspection. Indones J Electr Eng Comput Sci. Vol. 12, no. 3

  21. Wang B, Xie J, Li S, Wan Y, Fu S, Lu K (2018) Enabling high-performance onboard computing with virtualization for unmanned aerial systems", 2018 International Conference on Unmanned Aircraft Systems (ICUAS), Dallas, TX, 2018, pp. 202–211.doi: https://doi.org/10.1109/ICUAS.2018.8453368

  22. VMware_paravirtualization. [Online], available April 2020: https://www.vmware.com/content/dam/digitalmarketing/vmware/en/pdf/techpaper/VMware_paravirtualization.pdf

  23. Bazm M, Lacoste M, Südholt M et al (2019) Isolation in cloud computing infrastructures: new security challenges. Ann Telecommun 74:197–209

    Article  Google Scholar 

  24. VMWare. [Online], available April 2020: http://www.vmware.com

  25. Xen. [Online], available April 2020: https://xenproject.org/

  26. KVM “Kernel based Virtual Machines”. [Online] Available April 2020: https://www.redhat.com/fr/topics/virtualization/what-is-KVM

  27. Wei M, Lin Y, Lee C (2019) Performance optimization for InfiniBand virtualization on QEMU/KVM," 2019 IEEE International Conference on Cloud Computing Technology and Science (CloudCom), Sydney, Australia, 2019, pp. 19–26

  28. Masdari M, Zangakani M (2019) Green cloud computing using proactive virtual machine placement: challenges and issues. J Grid Computing. https://doi.org/10.1007/s10723-019-09489-9

    Article  Google Scholar 

  29. Sultan S, Ahmad I, Dimitriou T (2019) Container security: issues, challenges, and the road ahead. IEEE Access 7:52976–52996. https://doi.org/10.1109/ACCESS.2019.2911732

    Article  Google Scholar 

  30. Stephen S et al Container-based operating system virtualization: a scalable, high-performance alternative to hypervisors. SIGOPS Oper. Syst. Rev., pp 275–287. ISSN 0163–5980. https://doi.org/10.1145/1272998.1273025

  31. Maenhaut P, Volckaert B, Ongenae V et al (2020) Resource management in a containerized cloud: status and challenges. J NetwSyst Manage 28:197–246

    Article  Google Scholar 

  32. Á. Kovács 2017 "Comparison of different Linux containers," 2017 40th International Conference on Telecommunications and Signal Processing (TSP), Barcelona, pp. 47–51, doi: https://doi.org/10.1109/TSP.2017.8075934

  33. Marcel (2018) Performance evaluation of mikroTik-based virtual machine for small-scale network virtualization on VMware Platform. In: 2018 International Conference on Control, Electronics, Renewable Energy and Communications (ICCEREC), 2018, pp 154-158. https://doi.org/10.1109/ICCEREC.2018.8712000

  34. Lingayat A, Badre RR, Kumar Gupta A (2018) Performance evaluation for deploying docker containers on baremetal and virtual machine. In: 2018 3rd International Conference on Communication and Electronics Systems (ICCES), Coimbatore, India, «pp. 1019–1023, doi: https://doi.org/10.1109/CESYS.2018.8723998

  35. Openstack, Cloud operating system [Online], available June 2020: https://openstack.org

  36. Aruna K, Pradeep G (2020) Performance and scalability improvement using IoT-based edge computing container technologies. SN COMPUT SCI 1:91. https://doi.org/10.1007/s42979-020-0106-9

    Article  Google Scholar 

  37. Barika M, Garg S, Zomaya AY, van Lizhe Wang A, Moorsel, Rajiv R (2019) Orchestrating big data analysis workflows in the cloud: research challenges, survey, and future directions. ACM Comput Surv 52:1–37. https://doi.org/10.1145/3332301

    Article  Google Scholar 

  38. Socker: A wrapper for secure running of docker containers on slurm, A. Azab, [online] Available June 2020: https://github.com/unioslo/socker

  39. Raicu I, Foster IT, Zhao Y (2008) Many-task computing for grids and supercomputers", Many-Task Computing on Grids and Supercomputers 2008. MTAGS 2008. Workshop on, pp. 1–11

  40. Dominic L, Sukhpal SG, Peter G (2019) PRISM: an experiment framework for straggler analytics in containerized clusters. In Proceedings of the 5th International Workshop on Container Technologies and Container Clouds (WOC ’19).2019, pp. Association for Computing Machinery, New York, NY, USA, 13–18

  41. Chen J et al. (2018) Build and execution environment (BEE): an encapsulated environment enabling HPC applications running everywhere," 2018 IEEE International Conference on Big Data (Big Data), Seattle, WA, USA, 2018, pp. 1737–1746, doi: https://doi.org/10.1109/BigData.2018

  42. Smith JE, Nair R (2005) Virtual machines: versatile platforms for systems and processes. The Morgan Kaufmann Series in Computer Architecture and Design Series. Morgan Kaufmann Publishers; 2005

  43. Li X, Jiang Y, Ding Y, Wei D, Ma X, Li W (2010) Application research of docker based on mesos application container cluster," 2020 International Conference on Computer Vision, Image and Deep Learning (CVIDL), 2020, 476–479, Doi:https://doi.org/10.1109/CVIDL51233.2020.00-47

  44. Sergei A, Bohdan T, Franz G, Thomas K, Andre M, Christian P, Joshua L, Divya M, Dan O'Keeffe, Mark L. Stillwell, David G, David E, Rüdiger K, Peter P, Christof F (2016) SCONE: secure Linux containers with Intel SGX. In: Proceedings of the 12th USENIX Conference on Operating Systems Design and Implementation (OSDI'16). USENIX Association, USA, 689–703

  45. Docker Hub. [online], available 20 April 2020: https://hub.docker.com/

  46. Hu G, Zhang Y, Chen W (2019) Exploring the performance of singularity for high performance computing scenarios. In: 2019 IEEE 21st International Conference on High Performance Computing and Communications; IEEE 17th International Conference on Smart City; IEEE 5th International Conference on Data Science and Systems (HPCC/SmartCity/DSS), Zhangjiajie, China, 2019, pp. 2587–2593. https://doi.org/10.1109/HPCC/SmartCity/DSS.2019.00362

  47. Zhang J, Lu X, Panda DK (2017) Is singularity-based container technology ready for running MPI applications on HPC clouds", Proceedings of the l0th International Conference on Utility and Cloud Computing,

  48. Salomoni D et al (2018) INDIGO-DataCloud: aplatform to facilitate seamless access to e-infrastructures. J Grid Comput. 163:381–408

    Article  Google Scholar 

  49. Gomes J, Bagnaschi E, Campos I, David M, Alves L, Martins J, Pina J, López-García A, Orviz P (2018) Enabling rootless Linux Containers in multi-user environments: the udocker tool. Comput Phys Commun 232:84–97. https://doi.org/10.1016/j.cpc.2018.05.021

  50. Kurtzer GM, Sochat V, Bauer MW (2017) Singularity: scientific containers for mobility of compute. PLoS ONE 12(5):e0177459. https://doi.org/10.1371/journal.pone.0177459

  51. Silva V, Kirikova M, Alksnis G (2018) Containers for virtualization: an overview. Appl Comput Syst. 23(1):21–27

  52. De Lauretis L (2019) From monolithic architecture to micro-services architecture. 2019 IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW), Berlin, Germany, pp. 93–96, doi: https://doi.org/10.1109/ISSREW.2019.00050

  53. Yang M, Huang M (2019) An micro-services-based openstack monitoring tool. In: 2019 IEEE 10th International Conference on Software Engineering and Service Science (ICSESS), Beijing, China, pp. 706–709, doi: https://doi.org/10.1109/ICSESS47205.2019.9040740..

  54. Wilhelm H ( 2016) Micro-services for Scalability: Keynote Talk Abstract. In Proceedings of the 7th ACM/SPEC on International Conference on Performance Engineering (ICPE ’16). Association for Computing Machinery, New York, NY, USA, 133–134

  55. Li L, Tang T, Chou W (2015) A REST service framework for fine-grained resource management in container-based cloud," 2015 IEEE 8th International Conference on Cloud Computing, New York, NY, pp. 645–652, Doi: https://doi.org/10.1109/CLOUD.2015.91

  56. Jha DN, Garg S, Jayaraman PP, Buyya R, Li Z, Ranjan R (2018) A holistic evaluation of docker containers for interfering micro-services. In: 2018 IEEE International Conference on Services Computing (SCC), San Francisco, CA, pp 33–40. https://doi.org/10.1109/SCC.2018.00012

  57. Sampaio AR, et al. (2017) Supporting microservice evolution. 2017 IEEE International Conference on Software Maintenance and Evolution (ICSME), Shanghai, pp. 539–543, doi: https://doi.org/10.1109/ICSME.2017.63

  58. Cesar de la Torre C (2016) Containerized docker application lifecycle with microsoft platform and tools

  59. Foster I, Zhao Y, Raicu I, Lu S (2008) Cloud computing and grid computing 360-degree compared," 2008 Grid Computing Environments Workshop, Austin, TX, 2008, pp. 1-10, doi: https://doi.org/10.1109/GCE.2008.4738445

  60. Benedicic L, Cruz FA, Madonna A, Mariotti K Sarus(2019) Highly scalable docker containers for HPC systems. Benedicic L, Cruz FA, Madonna A., Mariotti K , ISC high performance 2019. Lecture notes in computer science, vol 11887. Springer, Cham, https://doi.org/10.1007/978-3-030-34356-9_5

  61. Menouer T, Darmon P (2019) Containers scheduling consolidation approach for cloud computing. In: Esposito C, Hong J, Choo KK (eds) Pervasive systems, algorithms and networks. I-SPAN. Communications in computer and information science, vol 1080, Springer, Cham. https://doi.org/10.1007/978-3-030-30143-9_15

  62. Perampalam P, Dick FA (2020) BEAVR: a browser-based tool for the exploration and visualization of RNA-seq data. BMC Bioinformatics 21:221

    Article  Google Scholar 

  63. Bella MRM, Data M, Yahya W (2018) Web server load balancing based on memory utilization using docker swarm. In" 2018 International Conference on Sustainable Information Engineering and Technology (SIET), 2018, pp. 220-223, doi: https://doi.org/10.1109/SIET.2018.8693212

  64. Marathon, orchestration tool for Mesos. [Online], availableJune 2020: https://mesosphere.github.io/marathon

  65. Saha P, Beltre A, Govindaraju M (2018) Exploring the fairness and resource distribution in an apache mesos environment. In: 2018 IEEE 11th International Conference on Cloud Computing (CLOUD), San Francisco, CA, 2018, pp. 434–441, doi: https://doi.org/10.1109/CLOUD.2018.000

  66. Zheng C, Tovar B, Thain D (2017) Deploying high throughput scientific workflows on container schedulers with makeflow and mesos," 2017 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID), 2017, pp. 130-139, doi: https://doi.org/10.1109/CCGRID.2017.9

  67. Bisong E. (2019) Containers and Google Kubernetes Engine. In: Building Machine Learning and Deep Learning Models on Google Cloud Platform. Apress, Berkeley, CA

  68. Medel V, Tolosana-Calasanz R, ÁngelBañares J, Arronategui U, Rana OF (2018) Characterising resource management performance in Kubernetes. Comput Electr Eng 68:286-297. https://doi.org/10.1016/j.compeleceng.2018.03.041

  69. Nexflow [Online], available Jully 2020: https://www.nextflow.io/

  70. Larsonneur E, Mercier J, Wiart N, Floch EL, Delhomme O, MeyerV (2018) Evaluating workflow management systems: a bioinformatics use case. In: 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Madrid, Spain, 2018, pp. 2773–277, https://doi.org/10.1109/BIBM.2018.8621141

  71. Casalicchio E, Iannucci S. The state‐of‐the‐art in container technologies: application, orchestration and security. Concurrency Computat Pract Exper. 2020; e5668. https://doi.org/10.1002/cpe.5668

  72. Ernst D, Bermbach D, Tai S (2016) Understanding the container ecosystem: a taxonomy of building blocks for container lifecycle and cluster management. Retrieved from the the: Proceedings of WoC. IEEE

  73. Madiha HS, Eduardo BF (2018). A reference architecture for the container ecosystem. In Proceedings of the 13th International Conference on Availability, Reliability and Security (ARES 2018). Association for Computing Machinery, New York

  74. Rodriguez MA, Buyya R (2019). Container‐based cluster orchestration systems: ataxonomy and future directions. Softw Pract Exp, 49(5), 698–719

  75. Bélair M, Laniepce S, Menaud J-M (2019) Leveraging kernel security mechanisms to improve container security: a survey. In Proceedings of the 14th International Conference on Availability, Reliability and Security (ARES '19). Association for Computing Machinery, New York, NY, USA, Article 76, 1–6

  76. Jenkins J, Shipman G, Mohd-Yusof J, Barros K, Carns P, Ross R (2017) A case study in computational caching micro-services for HPC. In: 2017 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), Lake Buena Vista, FL, 2017, pp

  77. Becker M. et al. (2020) Scaling genomics data processing with memory-driven computing to accelerate computational biology. In: Sadayappan P, Chamberlain B, Juckeland G, Ltaief H (eds) High performance computing. ISC High Performance 2020. Lecture Note

  78. Alexander S, Del Balso M (2018) "Horovod: fast and easy distributed deep learning in TensorFlow." arXiv preprint. https://arxiv.org/abs/1802.05799

  79. Vahi K et al (2019) Custom execution environments with containers in pegasus-enabled scientific workflows. In: 2019 15th International Conference on eScience (eScience), pp 281–290. https://doi.org/10.1109/eScience.2019.00039

  80. Liu W, Fan W, Li P, Li L ( 2018) Survey of big data platform based on cloud computing container technology. In: Barolli L, Terzo O (eds) Complex, intelligent, and software intensive systems. CISIS. Advances in intelligent systems and computing, vol 611. Springer, Cham. https://doi.org/10.1007/978-3-319-61566-0_90

  81. Aldinucci M et al (2018) HPC4AI: an AI-on-demand federated platform endeavour. In: Proceedings of the 15th ACM International Conference on Computing Frontiers (CF '18). Association for Computing Machinery, New York, NY, USA, pp 279–286. https://doi.org/10.1145/3203217.3205340

  82. Rao TR, Mitra P, Bhatt R et al (2019) The big data system, components, tools, and technologies: a survey. Knowl Inf Syst 60:1165–1245. https://doi.org/10.1007/s10115-018-1248-0

  83. Blamey B, Hellander A, Toor S (2019) Apache spark streaming, Kafka and HarmonicIO: A performance benchmark and architecture comparison for enterprise and scientific computing. In: Gao W., Zhan J., Fox G., Lu X., Stanzione D. (eds) Benchmarking, Measuri. «and optimizing. Bench 2019. Lecture notes in computer science, vol 12093. Springer, Cham

  84. Piras ME, Pireddu L, Moro M, Zanetti G (2019) Container orchestration on HPC clusters. In: Weiland M., Juckeland G., Alam S., Jagode H. (eds) High performance computing. ISC high performance 2019. Lecture notes in computer science, vol 11887. Springer,Cham

  85. Zhou N, Georgiou Y, Zhong L, Zhou H, Pospieszny M (2020) Container orchestration on HPC systems," 2020 IEEE 13th International Conference on Cloud Computing (CLOUD), , pp. 34–36, doi: https://doi.org/10.1109/CLOUD49709.2020.00017

  86. Ciubăncan M, Dulea M (2017) Implementing advanced data flow and storage management solutions within a multi-VO grid site," 2017 16th RoEduNet Conference: Networking in Education and Research (RoEduNet), TarguMures, pp. 1-4, doi: https://doi.org/10.1109/ROEDUNET.20

  87. Pablo Orviz F, Joao P, Álvaro López G et al (2018) umd-verification: automation of software validation for the EGI Federated e-infrastructure. J Grid Comput 16(4):683–696

    Article  Google Scholar 

  88. Alfonso DE, Carlos C, Amanda M, Germán. et al (2017) Container-based virtual elastic clusters. J Syst Softw 127:1–11

    Article  Google Scholar 

  89. OSG, Open Science GRID. [Online], available Jully 2020: https://opensciencegrid.org/

  90. HTcondor resource management. [Online], available Jully 2020: https://htcondor.readthedocs.io/en/latest/overview/index.html

  91. The Large Hadron Collider (LHC) - CERN. [Online], available Jully 2020: http://lhc.web.cern.ch

  92. Simone M, et al. (2020) CernVM-FS container image integration. J Phys Conf Ser. Vol. 1525. No. 1. IOP Publishing

  93. High throughput computing"HTC". [Online], available Jully 2020: https://htcondor.readthedocs.io/en/latest/overview/high-throughput-computing-requirements.html

  94. Singularity on HTC. [Online], available Jully 2020: https://indico.cern.ch/event/578972/contributions/2652740/attachments/1491278/2318170/ATLAS_Singularity_Status_1.pdf.

  95. Fernández-Del-Castillo E, Scardaci D, López García Á (2015) The EGI Federated Cloud e-Infrastructure. Proc Comput Sci, vol. 68, 2015. doi:https://doi.org/10.1016/j.procs.2015.09.235

  96. EGI: Advanced Computing for Research, presentation of Webinar. [Online], available Jully 2020: https://indico.egi.eu/event/5090/attachments/12961/15418/egi-containers-webinar-20200610.pdf

  97. EC3 (Elastic Cloud Computing Cluster). [Online], available July 2020 : https://egi-federated-cloud.readthedocs.io/en/latest/aod.html#ec3

  98. Moltó G, Caballer M, Pérez A, De Alfonso C, Blanquer I (2017) Coherent application delivery on hybrid distributed computing infrastructures of virtual machines and docker containers. In: 2017 25th Euromicro International Conference on Parallel, Distributed and Network-based Processing (PDP), p. 486-490. https://doi.org/10.1109/PDP.2017.29

  99. EGI, European GRID Infrastructure Foundation. [Online], available Jully 2020: https://www.egi.eu/

  100. AWS, Amazon Web Services.[Online], available August 2020: https://aws.amazon.com/

  101. Bisong E (2019) An overview of google cloud platform services. In: building machine learning and deep learning models on google cloud platform. Apress, Berkeley, CA. https://doi.org/10.1007/978-1-4842-4470-8

  102. Microsoft Azure. [Online], available August 2020: https://azure.microsoft.com/en-us/

  103. Chang H, et al. (2018) Performance evaluation of Open5GCore over KVM and Docker by using Open5GMTC," NOMS 2018 - 2018 IEEE/IFIP Network Operations and Management Symposium, Taipei, pp. 1–6, doi: https://doi.org/10.1109/NOMS.2018.8406141

  104. Fayos-Jordan R, Felici-Castell S, Segura-Garcia J, Lopez-Ballester J et al (2020) Maximo cobos, performance comparison of container orchestration platforms with low cost devices in the fog, assisting Internet of Things applications. J Netw Comput Appl 169:102788. https://doi.org/10.1016/j.jnca.2020.102788

  105. Mouradian C, Naboulsi D, Yangui S, Glitho RH, Morrow MJ, Polakos PA (2018) A comprehensive survey on fog computing: state-of-the-art and research challenges. IEEE Commun Surv Tutorials, vol.20, no.1, pp.416–464, Firstquarter2018. , https://doi.org/10.1109/COMST.2017.2771153

  106. Svorobej S, Bendechache M, Griesinger F, Domaschka J. (2020) Orchestration from the Cloud to the Edge. In: Lynn T, Mooney J, Lee B, Endo P (eds) The Cloud-to-thing continuum. Palgrave studies in digital business & enabling technologies., Palgrave Macmillan, Cham

  107. Kaur K, Garg S, Kaddoum G, Ahmed SH, Atiquzzaman M (2020) KEIDS: kubernetes-based energy and interference driven scheduler for industrial IoT in edge-cloud ecosystem. IEEE Internet Things J 7(5):4228–4237. https://doi.org/10.1109/JIOT.2019.2939534

  108. Huang D, Lu Y (2020) Improving the efficiency of HPC data movement on container-based virtual cluster. CCF Trans HPC 2:67–80. https://doi.org/10.1007/s42514-020-00025-w

    Article  Google Scholar 

  109. Riti (2018) Introduction to DevOps. In: Pro DevOps with Google Cloud Platform. A press, Berkeley, CA. https://doi.org/10.1001/978-1-48-42-3897-4_3

  110. Potdar AM, Narayan DG, Kengond S, Mulla MM (2020) Performance evaluation of docker container and virtual machine. Procedia Computer Science, vol 171, Pp 1419–1428, ISSN 1877–0509. https://doi.org/10.1016/j.procs.2020.04.152

  111. Vazhkudai SS, de Supinski BR, Bland AS, Geist A, Sexton J, Kahle J, Zimmer CJ, Atchley S, Oral S, Maxwell DE, et al. (2018) The design, deployment, and evaluation of the coral pre-exascalesystems.In: , Proceedings of the International Conference for High Performance Computing, Networking, Storage, and Analysis. IEEE Press, p. 52

  112. Pereira Ferreira A, Sinnott R (2019) A performance evaluation of containers running on managed kubernetes services. In: 2019 IEEE International Conference on Cloud Computing Technology and Science (CloudCom), , pp. 199–208, doi: https://doi.org/10.1109/CloudCom.2019.00038

  113. Bratterud A, Happe A, Duncan RAK (2017) Enhancing cloud security and privacy: the Unikernel solution. In: Eighth International Conference on Cloud Computing, GRIDs, and Virtualization, Athens, Greece. Curran Associates

Download references

Acknowledgements

This work was partially supported by the General Directorate of Scientific Research and Technological Development (DGRSDT, Algeria), under the PRFU project (ref: C00L07UN060120200003).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ouafa Bentaleb.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Bentaleb, O., Belloum, A.S.Z., Sebaa, A. et al. Containerization technologies: taxonomies, applications and challenges. J Supercomput 78, 1144–1181 (2022). https://doi.org/10.1007/s11227-021-03914-1

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11227-021-03914-1

Keywords

Navigation