Abstract
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. However, the cloud resources at the MEC on-site (access point) and edge site are restricted and insufficient mainly because of the operation and management constraints (e.g., limited space and capacity), particularly in the case of on-demand and dynamic service resource deployment. In this regard, we propose a selective MEC resource allocation scheme adopting a multitier architecture over a wide-area software-defined network (SDN) on the basis of our recent research work on virtual network slicing and resource orchestration. The proposed scheme provides an optimized MEC selection model considering end-to-end latency and efficient service resource utilization on the basis of the hierarchical MEC service architecture.
Highlights
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
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
Kubernetes works as a container manager, the Virtual dedicated network (VDN) system works as a virtual and KREONET-S works as a wide-area software-defined network (SDN) infrastructure, assuming that multiple network manager, and KREONET-S works as a wide-area SDN infrastructure, assuming that cloud computing nodes are located at the distributed Multi-access edge computing (MEC) sites
Summary
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. 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. 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. A resource integration and orchestration technology is required to select and allocate computing, storage, and network resources efficiently over the SDNized and containerized edge cloud infrastructure in order for dynamic resource management; MEC services can be enhanced with the improved quality of experience and service in a more intelligent and secure way.
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