Cloud, fog, and edge computing integration with future mobile Internet-of-Things (IoT) devices and related applications in 5G/6G networks will become more practical in the coming years. Containers became the de facto virtualization technique that replaced Virtual Memory (VM). Mobile IoT applications, e.g., intelligent transportation and augmented reality, incorporating fog-edge, have increased the demand for a millisecond-scale response and processing time. Edge Computing reduces remote network traffic and latency. These services must run on edge nodes that are physically close to devices. However, classical migration techniques may not meet the requirements of future mission-critical IoT applications. IoT mobile devices have limited resources for running multiple services, and client-server latency worsens when fog-edge services must migrate to maintain proximity in light of device mobility. This study analyzes the performance of the MiGrror migration method and the pre-copy live migration method when the migration of multiple VMs/containers is considered. This paper presents mathematical models for the stated methods and provides migration guidelines and comparisons for services to be implemented as multiple containers, as in microservice-based environments. Experiments demonstrate that MiGrror outperforms the pre-copy technique and, unlike conventional live migrations, can maintain less than 10 milliseconds of downtime and reduce migration time with a minimal bandwidth overhead. The results show that MiGrror can improve service continuity and availability for users. Most significant is that the model can use average and non-average values for different parameters during migration to achieve improved and more accurate results, while other research typically only uses average values. This paper shows that using only average parameter values in migration can lead to inaccurate results.

翻译：云、雾与边缘计算将结合未来移动物联网设备及其在5G/6G网络中的相关应用，在未来几年内变得更加实用。容器已取代虚拟内存（VM）成为事实上的虚拟化技术。融入雾-边缘计算的移动物联网应用（例如智能交通和增强现实）对毫秒级响应和处理时间提出了更高需求。边缘计算可减少远程网络流量和延迟。这些服务必须运行在物理上靠近设备的边缘节点上。然而，传统的迁移技术可能无法满足未来关键任务型物联网应用的需求。物联网移动设备在运行多项服务时资源有限，且当雾-边缘服务需随设备移动性保持邻近性而进行迁移时，客户端-服务器延迟会恶化。本研究分析了考虑多虚拟机/容器迁移时的MiGrror迁移方法与预拷贝实时迁移方法的性能。本文为所述方法建立了数学模型，并针对需以多容器形式（如微服务环境）实现的服务，提供了迁移指南与比较。实验表明，MiGrror方法优于预拷贝技术，且与传统实时迁移不同，能将停机时间保持在10毫秒以内，同时以最小带宽开销减少迁移时间。结果显示，MiGrror可提升用户的服务连续性与可用性。最重要的是，该模型在迁移过程中能使用不同参数的平均值和非平均值，以获得更优且更精确的结果，而其他研究通常仅使用平均值。本文表明，在迁移中仅使用平均参数值可能导致不精确的结果。