Improving Task Scheduling In Cloud Datacenters By Implementation Of An Intelligent Scheduling Algorithm

The need for mobile and online Apps and services has led to rapid growth in cloud computing services. The rapid increase in growth highlights the importance of reducing the time required for scheduling and efficiently utilizing resources in a dynamic setting. Consequently, numerous scheduling algorithms have been devised to address these problems by employing intelligent scheduling approaches, including Genetic Algorithms, greedy algorithm, Antlion Optimizer, Ant Colony optimization, and Cuckoo Intelligent Algorithm. This study provides an overview of intelligent optimization strategies, with a specific focus on the Cuckoo intelligent methodology. Additionally, it presents a proposed implementation of a Cuckoo-based cloud computing environment as an efficient algorithm that is projected to yield improved results in task scheduling.