A Hybrid Technique Using Genetic Algorithm and ANT Colony Optimization for Improving in Cloud Datacenter - Kaur, Mandeep; Agnihotri, Manoj (International Journal of Computer Sciences and Engineering, 2025)
Cloud computing is becoming popular day by day, due to its wide range of applications. As demand of cloud computing is increasing, it increases the number of request too. Thus providing high availability to its user is a challenging task. So load balancing techniques become good alternative of these techniques. In optimization issue, Genetic Algorithm (GA) and Ant Colony Optimization Algorithm (ACO) have already been referred to as excellent option method. GA is created by adopting the organic progress process, while ACO is encouraged by the foraging behavior of ant species. That paper has offered a hybrid GAACO based scheduling technique to improve the load balancing further. In this technique, GA can view and maintain the fittest ant in each period in most era and just unvisited spots will be evaluated by ACO. The overall objective of this paper is proposes hybrid GA-ACO based analytical model to enhance the results further.