Skip to main content
SpringerLink
Log in

Towards Orchestration of Cloud-Edge Architectures with Kubernetes

  • Conference paper
  • First Online:
Science and Technologies for Smart Cities (SmartCity 360 2021)

Included in the following conference series:

Abstract

Edge computing brings computational resources, reliable network infrastructure, and real-time capabilities closer to devices. Providing resources and workloads at the edge is mainly realized with container technology. The appropriate placement in terms of when, where, and how to provide containerized workloads is still an ongoing problem domain. Kubernetes is nowadays the state-of-the-art platform for containerized service orchestration to tackle these issues. Although Kubernetes misses capabilities like using real-time network metrics for scheduling and topology awareness, it is still used for realizing cloud-edge architectures. In this paper, we analyze current cloud-edge architectures implemented with Kubernetes and how they solve general requirements of edge computing and orchestration. Furthermore, we identify shortcomings in these implementations based on the fundamental requirements of edge computing and orchestration. Even if issues like obtaining network-related metrics and implementing topology awareness are solved well, other requirements like real-time processing of metrics, fault-tolerance, and the placement of container registries are in early stages.

All links were last followed on June, 26, 2021.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 99.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 129.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    https://www.statista.com/statistics/1101442/iot-number-of-connected-devices-worldwide/.

  2. 2.

    https://kubernetes.io/.

  3. 3.

    https://www.networkworld.com/article/2979570/microsoft-researcher-why-micro-datacenters-really-matter-to-mobiles-future.html.

  4. 4.

    It is even possible to run single-node clusters by attaching workloads to the master node; however, this should not be done in production environments.

  5. 5.

    https://kubernetes.io/docs/tasks/run-application/horizontal-pod-autoscale/.

  6. 6.

    https://kubernetes.io/docs/concepts/overview/components/.

  7. 7.

    https://kubernetes.io/docs/concepts/extend-kubernetes/.

  8. 8.

    https://kubeedge.io/en/.

  9. 9.

    https://baetyl.io/en.

  10. 10.

    https://github.com/openyurtio/openyurt.

  11. 11.

    https://iofog.org/.

  12. 12.

    https://kubernetes.io/docs/setup/best-practices/cluster-large/.

  13. 13.

    https://kubernetes.io/docs/tasks/extend-kubernetes/configure-multiple-schedulers/.

  14. 14.

    https://kubernetes.io/docs/setup/production-environment/.

  15. 15.

    https://kubernetes.io/docs/setup/production-environment/tools/kubeadm/ha-topology/.

  16. 16.

    https://kubernetes.io/docs/concepts/security/controlling-access/.

  17. 17.

    https://github.com/kubernetes-sigs/kubefed.

  18. 18.

    https://cloud.google.com/.

  19. 19.

    https://jelastic.com/.

References

  1. Aazam, M., Zeadally, S., Harras, K.A.: Offloading in fog computing for IoT: review, enabling technologies, and research opportunities. Futur. Gener. Comput. Syst. 87, 278–289 (2018)

    Article  Google Scholar 

  2. Ahmed, E., Rehmani, M.H.: Mobile edge computing: opportunities, solutions, and challenges. Futur. Gener. Comput. Syst. 70, 59–63 (2017)

    Article  Google Scholar 

  3. Al-Tarawneh, M.A.B.: Mobility-aware container migration in cloudlet-enabled IoT systems using integrated muticriteria decision making. Int. J. Adv. Comput. Sci. Appl. 11(9), 694–701 (2020)

    Google Scholar 

  4. Amaral, M., Polo, J., Carrera, D., Mohomed, I., Unuvar, M., Steinder, M.: Performance evaluation of microservices architectures using containers (2015)

    Google Scholar 

  5. Babou, C.S.M., Fall, D., Kashihara, S., Niang, I., Kadobayashi, Y.: Home Edge Computing (HEC): design of a new edge computing technology for achieving ultra-low latency. In: Liu, S., Tekinerdogan, B., Aoyama, M., Zhang, L.-J. (eds.) EDGE 2018. LNCS, vol. 10973, pp. 3–17. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-94340-4_1

    Chapter  Google Scholar 

  6. Bagchi, S., Siddiqui, M.B., Wood, P., Zhang, H.: Dependability in edge computing. Commun. ACM 63(1), 58–66 (2019)

    Article  Google Scholar 

  7. Barika, M., Garg, S., Zomaya, A.Y., Wang, L., Moorsel, A.V., Ranjan, R.: Orchestrating big data analysis workflows in the cloud. ACM Comput. Surv. 52(5), 1–41 (2019)

    Article  Google Scholar 

  8. Bilal, K., Khalid, O., Erbad, A., Khan, S.U.: Potentials, trends, and prospects in edge technologies: fog, cloudlet, mobile edge, and micro data centers. Comput. Netw. 130, 94–120 (2018)

    Article  Google Scholar 

  9. Bonomi, F., Milito, R., Zhu, J., Addepalli, S.: Fog computing and its role in the internet of things. In: Proceedings of the First Edition of the MCC Workshop on Mobile Cloud Computing - MCC 2012. ACM Press (2012)

    Google Scholar 

  10. Casalicchio, E.: Autonomic orchestration of containers: problem definition and research challenges. In: Proceedings of the 10th EAI International Conference on Performance Evaluation Methodologies and Tools. ACM (2017)

    Google Scholar 

  11. Casquero, O., Armentia, A., Sarachaga, I., Perez, F., Orive, D., Marcos, M.: Distributed scheduling in Kubernetes based on MAS for fog-in-the-loop applications. In: 2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA). IEEE (2019)

    Google Scholar 

  12. Eidenbenz, R., Pignolet, Y.A., Ryser, A.: Latency-aware industrial fog application orchestration with Kubernetes. In: 2020 Fifth International Conference on Fog and Mobile Edge Computing (FMEC). IEEE (2020)

    Google Scholar 

  13. ETSI: Mobile-edge computing - introductory technical white paper (2014). https://portal.etsi.org/Portals/0/TBpages/MEC/Docs/Mobile-edge_Computing_-_Introductory_Technical_White_Paper_V118-09-14.pdf

  14. Goethals, T., DeTurck, F., Volckaert, B.: Extending Kubernetes clusters to low-resource edge devices using virtual Kubelets. IEEE Trans. Cloud Comput. (2020)

    Google Scholar 

  15. Goethals, T., Volckaert, B., de Turck, F.: Adaptive fog service placement for real-time topology changes in Kubernetes clusters. In: Proceedings of the 10th International Conference on Cloud Computing and Services Science. SCITEPRESS - Science and Technology Publications (2020)

    Google Scholar 

  16. Haja, D., Szalay, M., Sonkoly, B., Pongracz, G., Toka, L.: Sharpening Kubernetes for the edge. In: Proceedings of the ACM SIGCOMM 2019 Conference Posters and Demos on - SIGCOMM Posters and Demos 2019. ACM Press (2019)

    Google Scholar 

  17. Han, Y., Shen, S., Wang, X., Wang, S., Leung, V.C.M.: Tailored learning-based scheduling for Kubernetes-oriented edge-cloud system (2021)

    Google Scholar 

  18. Hong, C.H., Varghese, B.: Resource management in fog/edge computing. ACM Comput. Serv. 52(5), 1–37 (2019)

    Article  Google Scholar 

  19. Hoque, S., Brito, M.S.D., Willner, A., Keil, O., Magedanz, T.: Towards container orchestration in fog computing infrastructures. In: 2017 IEEE 41st Annual Computer Software and Applications Conference (COMPSAC). IEEE (2017)

    Google Scholar 

  20. Javed, A., Heljanko, K., Buda, A., Framling, K.: CEFIoT: a fault-tolerant IoT architecture for edge and cloud. In: 2018 IEEE 4th World Forum on Internet of Things (WF-IoT), pp. 813–818. IEEE (2018)

    Google Scholar 

  21. Kaur, K., Garg, S., Kaddoum, G., Ahmed, S.H., Atiquzzaman, M.: KEIDS: Kubernetes-based energy and interference driven scheduler for industrial IoT in edge-cloud ecosystem. IEEE Internet Things J. 7(5), 4228–4237 (2020)

    Article  Google Scholar 

  22. Kayal, P.: Kubernetes in fog computing: feasibility demonstration, limitations and improvement scope: invited paper. In: 2020 IEEE 6th World Forum on Internet of Things (WF-IoT), pp. 1–6. IEEE (2020)

    Google Scholar 

  23. Klas, G.I.: Fog computing and mobile edge cloud gain momentum. Open Fog Consortium-ETSI MEC-Cloudlets (2015)

    Google Scholar 

  24. Morabito, R.: Virtualization on internet of things edge devices with container technologies: a performance evaluation. IEEE Access 5, 8835–8850 (2017)

    Article  Google Scholar 

  25. Mouradian, C., Naboulsi, D., Yangui, S., Glitho, R.H., Morrow, M.J., Polakos, P.A.: A comprehensive survey on fog computing: state-of-the-art and research challenges. IEEE Commun. Surv. Tutorials 20(1), 416–464 (2018)

    Article  Google Scholar 

  26. Naha, R.K., et al.: Fog computing: survey of trends, architectures, requirements, and research directions. IEEE Access 6, 47980–48009 (2018)

    Article  Google Scholar 

  27. Ogbuachi, M.C., Reale, A., Suskovics, P., Kovács, B.: Context-aware Kubernetes scheduler for edge-native applications on 5G. J. Commun. Softw. Syst. 16(1), 85–94 (2020)

    Article  Google Scholar 

  28. Pahl, C., Ioini, N.E., Helmer, S., Lee, B.: An architecture pattern for trusted orchestration in IoT edge clouds. In: 2018 Third International Conference on Fog and Mobile Edge Computing (FMEC). IEEE (2018)

    Google Scholar 

  29. Pahl, C., Lee, B.: Containers and clusters for edge cloud architectures - a technology review. In: 2015 3rd International Conference on Future Internet of Things and Cloud. IEEE (2015)

    Google Scholar 

  30. Premsankar, G., Francesco, M.D., Taleb, T.: Edge computing for the internet of things: a case study. IEEE Internet Things J. 5(2), 1275–1284 (2018)

    Article  Google Scholar 

  31. Qiu, Y., Lung, C.H., Ajila, S., Srivastava, P.: LXC container migration in cloudlets under multipath TCP. In: 2017 IEEE 41st Annual Computer Software and Applications Conference (COMPSAC). IEEE (2017)

    Google Scholar 

  32. Qiu, Y., Lung, C.H., Ajila, S., Srivastava, P.: Experimental evaluation of LXC container migration for cloudlets using multipath TCP. Comput. Netw. 164, 106900 (2019)

    Article  Google Scholar 

  33. Santos, J., Wauters, T., Volckaert, B., Turck, F.D.: Resource provisioning in fog computing: from theory to practice \({\dagger }\). Sensors 19(10), 2238 (2019)

    Google Scholar 

  34. Satyanarayanan, M., Bahl, P., Caceres, R., Davies, N.: The case for VM-based cloudlets in mobile computing. IEEE Pervasive Comput. 8(4), 14–23 (2009)

    Article  Google Scholar 

  35. Satyanarayanan, M.: Edge computing. Computer 50(10), 36–38 (2017)

    Article  Google Scholar 

  36. da Silva, D.M.A., Asaamoning, G., Orrillo, H., Sofia, R.C., Mendes, P.M.: An analysis of fog computing data placement algorithms. In: Proceedings of the 16th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services. ACM (2019)

    Google Scholar 

  37. Svorobej, S., Bendechache, M., Griesinger, F., Domaschka, J.: Orchestration from the cloud to the edge. In: Lynn, T., Mooney, J.G., Lee, B., Endo, P.T. (eds.) The Cloud-to-Thing Continuum. PSDBET, pp. 61–77. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-41110-7_4

    Chapter  Google Scholar 

  38. Taherizadeh, S., Stankovski, V., Grobelnik, M.: A capillary computing architecture for dynamic internet of things: orchestration of microservices from edge devices to fog and cloud providers. Sensors 18(9), 2938 (2018)

    Article  Google Scholar 

  39. Vaquero, L.M., Cuadrado, F., Elkhatib, Y., Bernal-Bernabe, J., Srirama, S.N., Zhani, M.F.: Research challenges in nextgen service orchestration. Futur. Gener. Comput. Syst. 90, 20–38 (2019)

    Article  Google Scholar 

  40. Vaquero, L.M., Rodero-Merino, L.: Finding your way in the fog: towards a comprehensive definition of fog computing. ACM SIGCOMM Comput. Commun. Rev. 44(5), 27–32 (2014)

    Article  Google Scholar 

  41. Varghese, B., Wang, N., Barbhuiya, S., Kilpatrick, P., Nikolopoulos, D.S.: Challenges and opportunities in edge computing (2016)

    Google Scholar 

  42. Velasquez, K., et al.: Fog orchestration for the internet of everything: state-of-the-art and research challenges. J. Internet Serv. Appl. 9(1) (2018)

    Google Scholar 

  43. Wang, J., Pan, J., Esposito, F., Calyam, P., Yang, Z., Mohapatra, P.: Edge cloud offloading algorithms: issues, methods, and perspectives. ACM Comput. Serv. 52(1), 1–23 (2019)

    Google Scholar 

  44. Wöbker, C., Seitz, A., Mueller, H., Bruegge, B.: Fogernetes: deployment and management of fog computing applications. In: NOMS 2018–2018 IEEE/IFIP Network Operations and Management Symposium. IEEE (2018)

    Google Scholar 

  45. Yousefpour, A., et al.: All one needs to know about fog computing and related edge computing paradigms: a complete survey. J. Syst. Archit. 98, 289–330 (2019)

    Article  Google Scholar 

  46. Yu, Z., Wang, J., Qi, Q., Liao, J., Xu, J.: Boundless application and resource based on container technology. In: Liu, S., Tekinerdogan, B., Aoyama, M., Zhang, L.-J. (eds.) EDGE 2018. LNCS, vol. 10973, pp. 34–48. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-94340-4_3

    Chapter  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Distributed Systems Group, University of Bamberg, Bamberg, Germany

    Sebastian Böhm & Guido Wirtz

Authors
  1. Sebastian Böhm
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Guido Wirtz
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sebastian Böhm .

Editor information

Editors and Affiliations

  1. Instituto Politécnico de Viana do Castelo, Viana do Castelo, Portugal

    Sara Paiva

  2. Auckland University of Technology, Auckland, New Zealand

    Xuejun Li

  3. Instituto Politécnico de Viana do Castelo, Viana do Castelo, Portugal

    Sérgio Ivan Lopes

  4. SRM Institute of Science and Technology, Chennai, India

    Nishu Gupta

  5. Howard University, Washington, DC, USA

    Danda B. Rawat

  6. Stoke-on-Trent, Birmingham, UK

    Asma Patel

  7. Politecnico di Milano, Milan, Italy

    Hamid Reza Karimi 

Rights and permissions

Reprints and permissions

Copyright information

© 2022 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Böhm, S., Wirtz, G. (2022). Towards Orchestration of Cloud-Edge Architectures with Kubernetes. In: Paiva, S., et al. Science and Technologies for Smart Cities. SmartCity 360 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 442. Springer, Cham. https://doi.org/10.1007/978-3-031-06371-8_14

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-06371-8_14

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-06370-1

  • Online ISBN: 978-3-031-06371-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation