Abstract
Task scheduling is a critical component in cloud computing, directly impacting the efficiency and performance of cloud environments. This paper presents a comparative performance analysis of four task scheduling algorithms: a hybrid credit-based resource-aware load balancing algorithm (HO-CB-RALB-SA), a conventional load balancing algorithm, an enhanced load balancing algorithm, and a locust-inspired algorithm. The hybrid approach integrates the Walrus Optimisation Algorithm (WOA) and Lyrebird Optimisation Algorithm (LOA), while the other algorithms represent nature-inspired and heuristic techniques. The evaluation focuses on three key metrics: makespan, resource utilisation, and balance percentage. By analysing these algorithms, the study identifies the strengths and limitations of each approach, providing insights into their effectiveness for cloud task scheduling. The results contribute to the selection and optimisation of task scheduling strategies tailored to diverse cloud computing needs and increase user satisfaction.