Edge Computing: Virtualization Techniques for Performance Optimization and Management Analysis

Edge Computing: Virtualization Techniques for Performance Optimization and Management Analysis

연구 분야: Networking

학회: International Conference on Pattern Recognition

Virtual machine management has become a vital aspect of efficient computing with the explosion in popularity of the Internet of Things (IoT). In edge computing, resources like computational power, memory, and network bandwidth vary according to the user's demand. The management of virtual machines is crucial, as it has a profound effect on performance in the edge computing environment. This study examines the significance of virtual machine management in edge computing, aiming to optimize performance and resource allocation. It discusses several virtualization techniques that utilize lightweight virtualization compared with conventional virtualization. Additionally, it delves into resource allocation techniques, including static and dynamic deployment, to ensure efficient workload distribution. Moreover, it delineates prospective performance measures to improve edge computing system efficiency. The significant findings discuss the progress made in this domain in the past five years. The study outcomes demonstrate that optimizing system performance depends on the effective administration of virtual machines, particularly in the context of IoT devices and edge computing systems with restricted resources. Overall, this study offers methods to enhance the performance of edge computing systems through virtualization techniques.