International Journal of Applied Science and Engineering
Published by Chaoyang University of Technology

Dhuha Basheer Abdullah, Wael Hadeed*

Department of computer science, University of Mosul, Hay Althaqafa, Mosul, Iraq

 

Download Citation: |
Download PDF


ABSTRACT

A new trend of advanced applications with high demands has emerged in recent years. Though cloud computing provides ripe management services with ubiquitous abilities, new needs and workloads decreed by new services tend to unmask their deficiencies. Edge computing is a new type of computing that brings cloud services closer to customers. In addition to that, edge computing reduces client/server latency significantly. The services must work on edge nodes that are physical as near to their customers as reasonable to achieve slight latencies. As a result, when a client relocates, a service should migrate across edge nodes to preserve proximity. Besides, migration of containers between edge nodes allows for many emerging use cases, reduces back-to-the-cloud, and optimizes resource management (for example, e-learning systems). In this paper, an algorithm for managing container execution has been proposed. A set of constraints are considered when migrating containers between nodes, such as resource availability, deadline time, and nodes location. When an event occurs, the container must be migrated from one node to another closest/best possible node is searched. The container live migration is used to get the best possible response time, reduce server return, and better manage resources.


Keywords: Edge computing, Container, Docker, Optimal decision, Live migration.


Share this article with your colleagues

 


REFERENCES

  1. Benomar, Z., Longo, F., Merlino, G., Puliafito, A. 2020. Cloud-based enabling mechanisms for container deployment and migration at the network edge. ACM Transactions on Internet Technology, 20. https://doi.org/10.1145/3380955

  2. Dhumal, A., Janakiram, D. 2020. C-balancer: a system for container profiling and scheduling. 1–10. http://arxiv.org/abs/2009.08912

  3. Gery, S.W. 1997. Direct fix of latitude and longitude from two observed altitudes. Navigation, Journal of the Institute of Navigation, 44, 15–24. https://doi.org/10.1002/j.2161-4296.1997.tb01935.x

  4. Govindaraj, K., Artemenko, A. 2018. Container live migration for latency critical industrial applications on edge computing. IEEE International Conference on Emerging Technologies and Factory Automation, ETFA, 2018-Septe(iii), 83–90. https://doi.org/10.1109/ETFA.2018.8502659

  5. H., N.S., Kumar, K.R.A., Shenoy, S.N., Rao, A.S., 2020. Data security in cloud environment based on comparative performance evaluation of cryptographic algorithms. International Journal of Advanced Trends in Computer Science and Engineering, 9, 4989–4997.

  6. Hadeed, W.W., Abdullah, D.B. 2021. Real-time based big data and e-learning: a survey and open research issues. AL-Rafidain Journal of Computer Sciences and Mathematics, 15, 225–243.

  7. Havanje, N.S., Kumar, K.R.A., Shenoy, S.N., Rao, A.S., Thimmappayya, R.K. 2022. Secure and reliable data access control mechanism in multi-cloud environment with inter-server communication security. Suranaree Journal of Science & Technology, 29.

  8. Kaur, H., Kaur, K. 2020. Live Migration of stateful processes across edge servers. International Journal of Recent Technology and Engineering, 8, 5207–5211. https://doi.org/10.35940/ijrte.e9850.038620

  9. Ketu, S., Mishra, P.K. 2021. Cloud, fog and mist computing in iot: an indication of emerging opportunities. IETE Technical Review (Institution of Electronics and Telecommunication Engineers, India), 0, 1–12. https://doi.org/10.1080/02564602.2021.1898482

  10. Kim, T., Al-Tarazi, M., Lin, J.W., Choi, W. 2021. Optimal container migration for mobile edge computing: algorithm, system design and implementation. IEEE Access, 9, 158074–158090. https://doi.org/10.1109/ACCESS.2021.3131643

  11. Kotikalapudi, S.V.N. 2017. Comparing live migration between linux containers and kernel virtual machine : investigation study in terms of parameters. February, 42. www.bth.se

  12. Ma, L., Yi, S., Li, Q. 2017. Efficient service handoff across edge servers via docker container migration. 2017 2nd ACM/IEEE Symposium on Edge Computing, SEC 2017. https://doi.org/10.1145/3132211.3134460

  13. Maheshwari, S., Choudhury, S., Seskar, I., Raychaudhuri, D. 2018. Traffic-Aware Dynamic Container Migration for Real-Time Support in Mobile Edge Clouds. International Symposium on Advanced Networks and Telecommunication Systems, ANTS, 2018-(December). https://doi.org/10.1109/ANTS.2018.8710163

  14. Nagesh Shenoy H, K.R. Anil Kumar, Rajgopal K.T., Abhishek S. Rao. 2020. An Audit on cloud architectures addressing data privacy and security concerns. International Journal of Advanced Science and Technology, 29, 6373–6382. Retrieved from http://sersc.org/journals/index.php/IJAST/article/view/20081

  15. Ngo, M.V., Luo, T., Hoang, H.T., Tony Quek, Q.S. 2020. Coordinated container migration and base station handover in mobile edge computing. 2020 IEEE Global Communications Conference, GLOBECOM 2020 - Proceedings. https://doi.org/10.1109/GLOBECOM42002.2020.9322368

  16. Puliafito, C., Vallati, C., Mingozzi, E., Merlino, G., Longo, F., Puliafito, A. 2019. Container migration in the fog: A performance evaluation. Sensors (Switzerland), 19, 1–22. https://doi.org/10.3390/s19071488

  17. Salaht, F.A., Desprez, F., Lebre, A. 2020. An overview of service placement problem in fog and edge computing. ACM Computing Surveys, 53. https://doi.org/10.1145/3391196

  18. Smimite, O., Afdel, K. 2020. Containers placement and migration on cloud system. International Journal of Computer Applications, 176, 9–18. https://doi.org/10.5120/ijca2020920493

  19. Vasconcelos, D.R., Andrade, R.M.C., Severino, V., De Souza, J.N. 2019. Cloud, Fog, or Mist in IoT? That is the qestion. ACM Transactions on Internet Technology, 19. https://doi.org/10.1145/3309709

  20. Wang, S., Xu, J., Zhang, N., Liu, Y. 2018. A survey on service migration in mobile edge computing. IEEE Access, 6, 23511–23528. https://doi.org/10.1109/ACCESS.2018.2828102


ARTICLE INFORMATION

Received: 2022-06-15
Revised: 2022-07-27
Accepted: 2022-08-17
Available Online: 2022-09-05


Cite this article:

Abdullah,D.B., Hadeed, W. Container live migration in edge computing: a real-time performance amelioration. International Journal of Applied Science and Engineering, 19, 2022121. https://doi.org/10.6703/IJASE.202209_19(3).007

 

 

 

 

  Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.

Other people also read ...

doaj logo

 

2.9
2023CiteScore
 
 
67th percentile
Powered by  Scopus
 
 

SCImago Journal & Country Rank

IJASE - Most Read Articles

IJASE - Most popular articles