Efficient Migration Technique for Load Balancing in Cloud
Nishant Mathur, Abhilasha Chauhan · 2024
The provisioning and use of resources has been modernized by cloud computing, which provides unmatched scalability and flexibility. To maintain optimal usage of resources and performance, load balancing, commonly known as the effective allocation of workloads among cloud servers remains a crucial concern. To locate server nodes experiencing high resource utilization or prospective bottlenecks, the migration approach makes use of real-time performance monitoring and predictive analytics. The suggested method intelligently migrates virtual machines (VMs) to better spread the workload across available resources when a server node is judged to be overcrowded or underutilized. The concept offers a cost–benefit analysis approach that takes into account things like migration overhead, server capacity, application requirements, and user experience to enable effective migration. The suggested solution aims to minimize service interruption and migration-related expenses while maximizing resource utilization and response time improvements by dynamically adjusting migration tactics depending on these criteria. The basic model also offers a fault-tolerant and safe migration procedure that takes into consideration potential data integrity problems and security threats in order to guarantee seamless transfer and load balancing. The method allays worries about data privacy and confidentiality by using encryption and authentication procedures to protect sensitive data during transfer. Extensive simulations and tests are carried out in various cloud settings to evaluate the usefulness of the suggested strategy, comparing its performance to conventional load balancing techniques. The results validate the potential of the suggested migration strategy for load balancing in cloud systems by showing substantial improvements in resource utilization, response times, and overall system efficiency. Effective load balancing strategies are essential for efficient resource allocation and user satisfaction as cloud infrastructures continue to grow and handle a wider range of workloads. This abstract makes a significant contribution to the development of load balancing methodologies in cloud computing by offering insightful information on the planning and execution of effective migration techniques that enable cloud providers to offer high-performance services while ensuring reliability and cost-effectiveness.