Task scheduling in cloud computing system by improved honey badger optimization algorithm with two dimensional and three dimensional fractals

Abstract

Cloud computing task scheduling is not only the foundation for ensuring the efficient operation of the cloud platform, but also an important means of improving service quality and reducing costs. With the continuous development of cloud computing technology, the requirements for intelligent and automated task scheduling are also increasing. To address the demand for more efficient and flexible computations, an enhanced honey badger algorithm (HBA) utilizing two dimensional and three dimensional fractals is introduced. The digging phase of the honey badger's foraging strategy is improved by using the mathematical expressions of two dimensional and three dimensional fractals in rectangular and polar coordinates, which enhances the algorithm's performance while speeding up its convergence. The optimal solution HBACBKS-Z was selected by verification on the benchmark functions. The optimization problem of task scheduling in cloud computing systems is divided into large-scale task scheduling and small-scale task scheduling. Experiments were conducted in these two cases by using HBACBKS-Z and other traditional swarm intelligence optimization algorithms. It has been proved that HBACBKS-Z has significant advantages in terms of total cost, time cost, load cost and price cost, and can effectively solve the task scheduling optimization problem of cloud computing systems of various sizes.