TY - JOUR
TI - Modelling of horse herd optimization based multi objective task scheduling approach in cloud computing environment
AU - Karim Faten K
AU - Ghorashi Sara
AU - Alkhalaf Salem
AU - Ben Ishak Anis
AU - Alshetewi Sameer
JN - Thermal Science
PY - 2025
VL - 29
IS - 2
SP - 1583
EP - 1595
PT - Article
AB - Cloud computing, which offers scalable and flexible resources, faces a key  challenge in task scheduling, directly impacting system performance and user  satisfaction. Effective scheduling is crucial for optimizing resource use  and reducing makespan. The NP-completeness of the task scheduling problem  complicates achieving optimal outcomes. Scheduling applications is critical  in cloud computing due to the need to map future tasks to resources in real  time. Many existing methods focus on makespan and resource consumption but  overlook factors like energy usage and migration time, which affect web  services. This study proposes a horse herd optimization-based  multi-objective task scheduling approach (HHO-MOTSA) to address these gaps.  The HHO-MOTSA aims to minimize makespan, energy usage, and cost by modelling  the social behaviors of horses, including grazing, hierarchy, sociability,  and defense mechanisms. A fitness function helps evaluate solutions, where a  low value indicates minimized energy, makespan, and cost. Performance tests  using CloudSim show that HHO-MOTSA outperforms other methods in effec­tive  task scheduling.