Provisioning of Live Container Migration in Edge/Cloud Environments: Techniques and Challenges
Containers have become increasingly popular in the virtualization landscape. Their lightweight nature and fast deployment behavior make them an efficient alternative to traditional hypervisor-based virtual machines. In IoT applications and edge/cloud deployment, the live container migration can sub...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Yayasan Pendidikan Riset dan Pengembangan Intelektual (YRPI)
2025-06-01
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| Series: | Journal of Applied Engineering and Technological Science |
| Subjects: | |
| Online Access: | http://journal.yrpipku.com/index.php/jaets/article/view/6675 |
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| Summary: | Containers have become increasingly popular in the virtualization landscape. Their lightweight nature and fast deployment behavior make them an efficient alternative to traditional hypervisor-based virtual machines. In IoT applications and edge/cloud deployment, the live container migration can substantially reduce computing system overheads by minimizing the migration time and transmitting minimum memory pages from the source host without interrupting the service process. Until today, there has been a lack of comprehensive research discussing live container migration in the IoT domain and investigating the challenges of representing them in the edge/cloud environment. This survey presents cutting-edge articles that involve a live container migration approach. This survey aims to boost current knowledge, identify best practices, and highlight the challenges of live container migration in the IoT and edge/cloud environments, which will contribute to the advancement of container technology, as well as the optimization of deployment practices. The survey results indicate that selecting a suitable container engine relies heavily on the workload characteristics in the edge/cloud environment, particularly given the constraintions of live container migration. The survey highlights the direct and indirect challenges that influence container migration and proposes machine learning and blockchain as potential solutions.
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| ISSN: | 2715-6087 2715-6079 |