Toward a Container Migration Data-Auditing Mechanism for Edge Computing Environment

Toshihiro Uchibayashi, Bernady Apduhan, Takuo Suganuma, Masahiro Hiji

Research output: Chapter in Book/Report/Conference proceedingConference contribution


With the widespread use of IoT sensors and devices, it has become common to store data in the cloud. The huge and various types of data with different purposes and forms are not directly stored in the cloud but are sent to the cloud via edge computing devices. Applications are running in containers and VMs to collect data from edge computing devices and sent to the cloud. However, the current deployment and migration mechanisms for containers and VMs does not consider the conventions and regulations of the applications and data they contain. The problem is that it is easy to deploy or migrate a container and VM even if the edge computing device to which it is deployed or migrated violates the licensing terms of the application it contains, the terms of the organization, or the laws and regulations of the country in which it is located. We previously proposed a data-auditing migration control mechanism for VMs. The same problem was expected with containers as the number of edges increased. Therefore, this paper proposed a data-auditing mechanism for container migration. Implementation and evaluation of the proposed system in an edge computing environment showed that adding the proposed mechanism has minimal impact on migration time and is sufficiently practical.

Original languageEnglish
Title of host publicationComputational Science and Its Applications - ICCSA 2022 Workshops, Proceedings
EditorsOsvaldo Gervasi, Beniamino Murgante, Sanjay Misra, Ana Maria A.C. Rocha, Chiara Garau
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages13
ISBN (Print)9783031105449
Publication statusPublished - 2022
Event22nd International Conference on Computational Science and Its Applications , ICCSA 2022 - Malaga, Spain
Duration: Jul 4 2022Jul 7 2022

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13379 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference22nd International Conference on Computational Science and Its Applications , ICCSA 2022

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science


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