<p>Virtual Machine (VM) live migration enables the seamless transfer of active VMs between physical hosts without disrupting service or causing downtime in cloud computing environments. The increasing demand for cloud computing services has led to a significant rise in energy consumption, contributing to environmental concerns and operational costs due to the need for additional resources. This can result in increased energy consumption, further exacerbating environmental sustainability concerns. Although existing approaches have made significant progress in this field, several issues persist, including the frequent neglect of energy efficiency, leading to unnecessary expenses and environmental damage. This paper proposes the Enhanced Energy-Efficient Scheduling Algorithm (EEESA) for VM consolidation in cloud computing. EEESA aims to reduce communication overhead and promote energy-efficient decisions while optimizing VM migration to minimize energy consumption. This paper introduces EEESA, an enhanced energy-efficient scheduling algorithm designed to optimize live virtual machine (VM) migration for sustainable cloud computing. The proposed approach leverages workload prediction, real-time resource monitoring, and adaptive migration strategies to improve energy efficiency without compromising service performance. Experimental evaluations demonstrate that EEESA effectively reduces overall energy consumption by 40–45%, CPU utilization by 50–60%, and network traffic by 30–40%, thereby validating its potential for greener and more cost-efficient cloud data center operations. Simulation results in CloudSim show significant improvements: EEESA_CU optimizes CPU utilization by 50–60%, EEESA_NT improves network traffic bandwidth by 30–40%, and EEESA_EC reduces energy consumption by 40–45%. This work contributes to a more sustainable and cost-effective cloud computing framework.</p>