## 2 Related Works
### Packet Processing Solutions and Related Research
On the other hand, it has been found that DPDK is a suitable solution to apply to IoT environments as it is open source, works in the cloud environment and supports x86-based PC processors and various Linux distributions and general NICs. But there are several drawbacks associated with the development of a DPDK-enabled network system. When DPDK is used, the NIC is no longer recognized by the Linux kernel. In other words, a DPDK-enabled network system cannot benefit from various network processing functions that have already been implemented in the kernel's network stack [21]. The proposed architecture is basically the same as the SDN, and network slicing technologies that enable flexible network control by separating the two planes have been proposed in several advanced studies and applications. For example, [PERSON] et al. [22] proposed a multicore fast Ethernet switch based on DPDK, and [PERSON] et al. [23] proposed an SDN architecture in an LTE environment. [PERSON] et al. [24] applied the DPDK to an OpenFlow software switch. These previous studies applied SDN and DPDK in order to improve packet forwarding performance and provide flexibility, but their application was limited to the general Ethernet switch. On the other hand, several efforts have been made to employ SDN techniques in IoT environments. [PERSON] et al. [25] described a prototype for slicing home networks in an IoT environment. It slices a physical network into multiple layers to isolate the traffic and bandwidth between providers. [PERSON] et al. [26] proposed an SDN controller and roles for the controller such as resource matching and flow scheduling. In addition to these papers, there have been a number of studies on using an SDN controller for the efficient orchestration of network resources [27; 28; 29]. Although these studies provide valuable SDN architectures for IoT environments and efficient methods for developing and deploying an SDN controller, there has been little work done on building a high-performance data plane and application in the healthcare domain. From a data scale perspective, when a large number of things generate huge messages, the area of big data faces similar challenges as the area of IoT. In this area, many researchers are attempting to address the problem of handling this large amount of data [30]. [PERSON] et al. [31] proposed a \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Features** & **Vanilla PF\_RING** & **PF\_RING ZC** & **DPDK** & **6 WINDGate** \\ \hline Software base & O & O & O & O \\ Open source & O & X & O & X \\ Universality & O & O & O & O \\ Cloud & O & O & O & O \\ Bypass Network Stack & \(\triangle\) & O & O & O \\ Security & X & X & O & O \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Features of the packet processing solutions. big data architecture which focused on analyzing time-critical data using clusters of machines and extended online and offline analytic tools. [PERSON] et al. [32] proposed a compression algorithm for a surveillance system in IoT. This approach aims to enable the rapid transmission of captured media data from the sensors to user's surveillance system. To achieve this, it employs a video compression format. While it is obvious that methods for improving analysis of performance and for compressing data to be sent would be valuable in terms of guaranteeing system scalability, our approach is focused on addressing the scalability problem by improving the I/O performance of each single network node. The aims of this paper are (1) to separate the control plane and the data plane, (2) to apply DPDK to the data plane in order to improve message forwarding performance, (3) to cast complex and time-intensive jobs for processing signaling messages on the control plane, (4) to provide a method for synchronization between the two planes, and (5) to present a practical application of IoT in the healthcare domain.