## 3 Technology, Hardware and Software of Edge Computing
### Virtual Technology of Containers
Finally, Kubernetes [109] is an open-source platform that manages the entire lifecycle of applications by organizing containers and hosting both VM- and container-based applications. Kubernetes optimizes resource usage by automating deployment, scaling, and maintenance, enabling rapid deployment of custom applications [110]. \begin{table}
\begin{tabular}{c c c c} \hline
**Ref. No** & **Container Technology** & **Edge Node Hardware** & **ARM Architecture** \\ \hline
[91] & Docker & Raspberry Pi 3 Model B & Not specified \\
[99] & Docker, Containerd & Raspberry Pi 4 Model B and Raspberry Pi 3 & ARM v8 \\
[100] & Docker & Raspberry Pi 3s & ARM Cortex-A53 \\
[101] & KubeEdge, Kubernetes, Docker & ARM64 4-core CPU & ARM64 \\
[102] & KubeEdge & Jetson AGX Xavier, Raspberry Pi 3 & ARM64 \\
[103] & Kubernetes & Raspberry Pi & Not specified \\
[104] & Docker & Raspberry Pi 4 & ARM64 \\
[105] & Container (Not specified) & Apple Mac Mini M1 2020 with Raspberry Pi & ARM64 \\  & & and 16 GB memory & \\  & & A Samsung Exynos 5250 SoC with 1.7 GHz & \\
[106] & Docker & Cortex A15 CPU and a non-virtualized host & ARMv7 \\  & & with 2 GB of memory & \\
[107] & Kubernetes (K3S), Docker & Raspberry Pi 4 B+ & ARM,x86 \\
[108] & Kubernetes & Raspberry Pi & ARM \\ \hline \end{tabular}
\end{table} 
Table 4: ARM processor-based container technologies and edge hardware. In summary, container-based virtualization technologies play a crucial role in improving the efficiency, scalability, and flexibility of EC and FC environments. By minimizing latency, optimizing resource usage, and supporting diverse hardware architectures, containers and orchestration tools such as Kubernetes have become indispensable in modern EC infrastructures. These advancements are essential in achieving real-time processing and service continuity, particularly in resource-constrained edge environments. Container Isolation Technology  
Containers enhance the efficiency of application management in EC environments. Containers improve application management in edge environments [111] by utilizing a single core and providing multiple isolated environments with lower overhead compared to VMs [112]. However, containers face limitations in security and isolation. To overcome these challenges, Unikernel, with its simplified architecture, offers higher security and stronger isolation [113]. Some EC systems adopt a hybrid virtualization mode that combines both VMs and containers to manage hardware resources and application services. Table 5 provides examples of virtualization technologies used in EC. Container-based EC systems have been increasingly adopted for various EC applications due to their ability to run efficiently on low-resource devices. For example, a container-based edge system was implemented on an ARM device in [124], where images were acquired through a container runtime/engine, processed locally, and subsequently transmitted to the cloud for storage and further analysis. This approach highlights the potential of containerized environments in optimizing local data processing and cloud integration. Container runtimes such as Docker and Containerd are essential technologies for lightweight, efficient EC systems. In [125], two popular container runtime technologies, Docker and Containerd, were evaluated on Raspberry Pi 3 and 4 devices. Docker, owing to its lightweight nature, proved suitable for low-performance IoT devices, offering robustness, simplicity, and portability, while Containerd's open-source runtime further enhanced these advantages. In addition to container runtimes, the performance of various ARM-based single-board processors has also been analyzed in the context of containerized applications. A study in [91] evaluated Docker containers on five ARM-based processors, including Raspberry Pi 2 Model B, Raspberry Pi 3 Model B, Odroid C1+, Odroid C2, and Odroid XU4. The findings emphasized the need to consider both task scheduling and containerization to optimize application execution efficiency of applications on edge servers.