# Dynamic Virtual Network Slicing and Orchestration for Selective MEC Services over Wide-Area SDN
## 1 Introduction  
Recently, data traffic is increasing explosively as a variety of user equipment (UE) and intelligent devices such as smartphones, tablets, smart cars, and smart home devices go hand in hand with the evolution of cloud computing and network softwarization technologies. With the increase in the network diversity and complexity to manage multiple devices and to optimize the distribution and delivery of increasing amounts of data traffic, the efficient operation and management of network service resources becomes complicated. In order to overcome this problem, as a way of applying automation and intelligence to network infrastructure, the software-defined network (SDN) is evolving for dynamic and virtualized networking services, efficient network management, and cost-saving benefits in network deployment and operations [1, 2]. The SDN can manage and control network resources using a logically centralized controller that is separated from the data transmission layer called the data plane. For example, OpenFlow is an SDN technology to abstract and control the flow table in OpenFlow-enabled switches, adjusting data delivery paths on the basis of flow information [3]. An SDN controller acts like a network operating system (NOS). It monitors and collects network status and configuration data in real time to evaluate the global network topology while making network devices dynamically programmable. In this procedure, network automation and intelligence can be provided with an SDN, and one of the latest technological trends of SDNs is to pursue network resource virtualization and dynamic network slicing for automated and intelligent network management integrated with machine learning and deep learning technologies [4, 5]. By applying network automation and intelligence to network infrastructure, the collected network big data (e.g., logs, flows, events, and status) are analyzed by machine learningand deep learning models, and exploited for configuration, management, control, and orchestration of physical and virtual network resources. As a use case in the network virtualization and orchestration, KREONET-S (Korea Research Environment Open Network Softwarization) was developed to operate as a wide-area SDN infrastructure spanning five regions in South Korea, two regions in the United States, and one region in China, adopting OpenFlow as its southbound interface [6; 7]. Virtual dedicated network (VDN) and VDN orchestrator (VDNO) applications are being developed and deployed over KREONET-S to provide end-to-end virtual network slicing and automated orchestration capability for UE, end-hosts, and cloud resources, gaining high quality of data transmission and secure end-to-end communication services enabled by dynamic and dedicated resource (e.g., network bandwidth) provisioning. In addition, considering cloud computing as another evolutionary information and communications technology (ICT) shift, multi-access edge computing (MEC) has become an essential technology for collecting, analyzing, and processing data generated by widely distributed user equipment (UE), wireless end-hosts, Internet of things (IoT) sensors, etc., providing real-time and high-quality networking services with ultralow end-to-end latency guaranteed between various user devices and edge cloud computing nodes. The European Telecommunication Standard Institute (ETSI) MEC ISG [8; 9; 10] is primarily involved in the standardization efforts of MEC which is considered a key component of future fifth- and sixth-generation (5G and 6G) systems to meet the requirements of telecommunication operators in terms of flexibility and reconfigurability for the increasing traffic demand [11; 12]. MEC brings processing and storage capabilities to the edge of the network to inspire the development of new IoT applications and services through intelligent and big data analytics [13], and to offload the applications demanding huge processing resources from mobile devices to the edge computing cloud [14].