## 2 Related Works
### Edge-Related Technologies Analysis  
To resolve latency and load congestion issues in conventional centralized cloud computing, computing resource decentralization has been widely studied and developed via many approaches, such as Fog Computing, Mobile Edge Computing, Cloudlet, and Edge Computing. Table 1 summarizes current edge-related technologies. The edge-related technologies demand the cooperation of cloud and network technologies. Network nodes are usually under the control of network providers. The computing resources on the edge of the network can be defined as a set of network nodes and computing nodes in close proximity to the user-side. On the other end, CSPs apply cloud technologies to IoT gateways. Combining those approaches can reduce network latency and increase the QoS [2; 31; 32; 33; 34; 35; 36; 37; 32; 3; 31; 32; 33; 34; 35; 36; 37]. However, each of those techniques views the problem slightly differently, and this can interfere with the understanding of edge nodes in this paper. Therefore, an analysis of relationship between the edge-related technology is necessary. Edge-related technologies are still being studied including distributed storage and computational resources or infrastructure [1; 38] and edge, regional, and central clouds within a network topology [39]. \"Edge Computing\" is often used as a generic term [8]. Figure 1 shows the key features available within conventional cloud computing and edge-related technologies. Most of the technologies currently in research and development will deploy infrastructure closer to users based on virtualization technology of cloud computing. Multi-access Edge Computing could be more relevant to radio access networks (RANs) than other technologies. Edge Computing is more concerned with IoT than any other technology. Fog Computing could be aimed at providing reliable services in certain areas, and Cloudlet is considered to be the cornerstone of edge-related technologies [3; 37; 5; 8; 9; 31; 32]. Based on the analysis, we derived a resource-limited edge node, which has minimal cloud and network features, such as virtualization, context awareness, user-proximity, and network compatibility. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Issued by** & **Concept** & & **Definition** \\ \hline \multirow{4}{*}{CISCO 2011} & Fog Computing (FC) & \(\bullet\) & ends the cloud to the edge of networks, in particular wireless networks for the Internet of Things (IoT). \\  & Fog Computing (FC) & \(\bullet\) & pushes the computing applications, data, and services away from centralized nodes to the network edge, enabling analytics and knowledge generation to occur close to the data sources. \\ \hline \multirow{4}{*}{ETSI 2014} & Mobile Edge Computing (MEC) & \(\bullet\) & pushes the cloud computing capabilities close to the Radio Access Networks in 4G, 5G. \\  & Mobile Edge Computing (MEC) & \(\bullet\) & renamed to Multi-access Edge Computing in 2016. \\ \hline \multirow{2}{*}{Carnegie Mellon Univ. 2013} & \multirow{2}{*}{Cloudlet} & \(\bullet\) & is to “bring the cloud closer to the users”. \\  & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 1: A summary of edge-related technologies. In addition, the edge-related technologies are obviously important as next-generation computing technologies. By 2024, mobile technology subscriptions will reach 8.9 billion, of which 1.5 billion will be 5G, and video will account for around 74% of mobile data traffic [40]. The amount of mobile data traffic in 2022 (75.7 exabytes per month, 1 EB \(\approx\) 1,000,000 TB) will be 6.6 times higher than in 2017 (11.2 EB) [41]. Enterprises and academia are actively working to settle the traffic of wireless access networks so that it can emerge as 5G by 2020. As an integral part of 5G, the convergence of network and cloud computing technologies is essential to providing a variety of services, including dynamic content delivery, AR and VR, connected vehicles, and video streaming.