Hybrid electro search with genetic algorithm for task scheduling in cloud computing

Ain Shams Engineering Journal

P. Karthikeyan¹  S. Velliangiri²  D. Baswaraj³  V.M. Arul Xavier⁴ 

[1] Corresponding author.;Department of Computer Science and Engineering, CMR Institute of Technology, Hyderabad, Telangana, India;Department of Computer Science and Engineering, Karunya Institute of Technology and Sciences, Coimbatore, India;Department of Computer Science and Engineering, Presidency University, Bangalore, Karnataka, India;

关键词: Cloud computing;    Task scheduling;    Electro-search algorithm;    Genetic algorithm;   

DOI  :  

来源: DOAJ

【 摘 要 】

Cloud computing is on-demand Internet-based computing, which is a highly scalable service adopted by different working and non-working classes of people around the globe. Task scheduling one of the critical applications used by end-users and cloud service providers. The significant challenging in the task scheduler is to find an optimal resource for the given input task. In this paper, we proposed Hybrid Electro Search with a genetic algorithm (HESGA) to improve the behavior of task scheduling by considering parameters such as makespan, load balancing, utilization of resources, and cost of the multi-cloud. The proposed method combined the advantage of a genetic algorithm and an electro search algorithm. The genetic algorithm provides the best local optimal solutions, whereas the Electro search algorithm provides the best global optima solutions. The proposed algorithm outperforms than existing scheduling algorithms such as Hybrid Particle Swarm Optimization Genetic Algorithm (HPSOGA), GA, ES, and ACO.

【 授权许可】

Unknown