An IFWA-BSA Based Approach for Task Scheduling in Cloud Computing

• Published in: Journal of ICT Standardization Vol. 11; no. 1; p. 45
• Main Author: Li, Xiaoxia
• Format: Journal Article
• Language: English
• Published: Tokyo River Publishers 2023
• Subjects: Algorithms; Ant colony optimization; Cloud computing; Communication; Energy consumption; Fireworks; Genetic algorithms; Optimization; Quality of service; Scheduling; Task scheduling
• ISSN: 2245-800X; 2246-0853; 2246-0853
• DOI: 10.13052/jicts2245-800X.1113

Establishing an efficient cloud computing task scheduling model is the object of many scholars’ research. In view of the low scheduling efficiency in cloud computing task scheduling, we propose a cloud computing task scheduling algorithm based on the fusion of the Fireworks Algorithm and Bird Swarm Algorithm (IFWA-BSA). Firstly, we describe the cloud computing task scheduling model based on time and cost constraint functions, secondly, we use chaotic backward learning and Coasean distribution for optimization in FWA initialization; we set thresholds for the radius of core fireworks and non-core fireworks for optimization; we filter the IFWA individuals after each iteration by BSA algorithm, and finally, we use the IFWA-BSA algorithm is used in cloud computing task scheduling model to solve the optimal solution. In the simulation experiments, IFWA-BSA has obvious advantages over ACO, PSO and FWA in the comparison of execution time and consumption cost indexes, which reduces the scheduling time and cost of cloud computing.