Brain Drain Optimization: a Novel Approach for Task Scheduling in the Cloud Computing

These days, Cloud Computing is widely used in different applications such as Civis Analytics and AWS (Amazon Web Services). Through the virtualization of hardware and software, Cloud Computing delivers various services to users over the Internet. The main challenge of providing satisfactory quality of service to the users is workflow scheduling, an NP-hard problem that has been a topic of much research. In this paper, BRADO, a recently-developed swarm intelligence algorithm, has been introduced for allocating and scheduling tasks to appropriate resources. This proposed algorithm aims to minimize the total execution time of the whole workflow, known as makespan. The performance of this proposed algorithm has been evaluated using the CloudSim Plus toolkit. Moreover, the results have been compared with some well-known algorithms, including PSO and SA. Our findings show the superiority of the BRADO algorithm in allocating and scheduling tasks.