DYNAMIC CLOUD MOBILITY: ANALYZING VIRTUAL MACHINE MIGRATION STRATEGIES

Abstract

Virtual machine (VM) migration has become a critical technique in cloud computing, enabling load balancing, fault tolerance, and efficient resource utilization. Despite its widespread adoption, the effectiveness of VM migration strategies varies significantly depending on system architecture, workload characteristics, and network conditions. This study analyzes the performance and efficiency of various VM migration approaches, including live and nonlive migration, under diverse cloud scenarios. The proposed evaluation framework measures key metrics such as migration time, downtime, energy consumption, and network overhead to determine the optimal strategies for different use cases. Experimental results demonstrate that live VM migration techniques minimize service disruption and improve resource allocation, while non-live migration can be suitable for maintenance-heavy operations with lower time sensitivity. The findings highlight the importance of selecting appropriate migration strategies to enhance cloud performance, resilience, and operational efficiency, offering practical insights for cloud service providers and system architects.