Distributed Edge Cloud Proposal Based on VNF/SDN Environment

The integration of lightweight virtualization and distributed management techniques effectively addresses various challenges in edge cloud environments, including optimizing service provision and reducing energy consumption. As the ICT sector transitions from traditional cloud computing to edge cloud to enhance proximity, it has adopted hypervisor-based virtualization. The emergence of beyond 5G systems, characterized by the need for autonomous orchestration, decentralized processing, ultra-low latency, and high throughput, necessitates a shift towards a distributed cloud system with autonomous functionalities. This infrastructure enables proactive control and management of network functions, allowing the delivery of services and microservices through a preconfigured setup at the edge. In regions prone to geographical instability, where network integrity can be compromised by natural disasters like earthquakes and tsunamis, establishing a robust, self-managing network is crucial. Such a network should be capable of independently providing services using local resources, functioning autonomously without external reliance, and effectively managing itself. This paper introduces NerveNet-VNF, a concept focusing on container-based virtualization of network functions. This system is coupled with SDN technology and integrated with a Dynamic Load Balancing (D-LB) system within a distributed cloud architecture. This integrated solution enables the hosting, management, and provisioning of local microservice requirements. Additionally, it introduces a new concept for splitting network functionality based on containers compared to the traditional abstract splitting system. Evaluation of this system demonstrates improvements in latency and throughput. Notably, there is a 20% reduction in NerveNet-VNF request execution time compared to the pre-existing NerveNet network. Moreover, integrating the distributed SDN controller technique into the distributed cloud system (HEC) has reduced latency by 88.91% and improved throughput by 28.48%.