Load Balancing in Cloud Computing Using Modified ANT Colony Algorithm

Recent advancements in computing technology like cloud computing and edge computing brings new directions in research. However, there are several issues like security, load balancing, and fault tolerance that need to be addressed in cloud system before used in a real-life scenario. The load balancer objective is to dynamically allocate incoming tasks to a virtual machine while optimizing several parameters. This work focuses on designing a load balancer based on ant colony optimization (ACO) to improve the performance of cloud cloud-based system. The system dynamically identifies and selects a virtual machine having lesser load for allocating tasks, considering various parameters. The suggested approach is predicated on a dynamic forwarding technique motivated by ACO. The experimental results validate how ACO based load balancer improves the response time of the system. The result analysis shows ACO based load balancer has improved response time by 30% in comparison to the classical load balancer. It demonstrates the positive outcome of ACO based load balancer.