Affiliation:
1. Banasthali Vidyapith, India
Abstract
Nowadays, Cloud Computing has become the most attractive platform, which provides anything as a Service (XaaS). Many applications may be developed and run on the cloud without worrying about platforms. It is a big challenge to allocate optimal resources to these applications and satisfy user's quality of service requirements. Here, in this paper, a Deadline Constrained Time-Cost effective Salp Swarm Algorithm (DTC-SSA) is proposed to achieve optimized resource allocation. DTC-SSA assigns the user's task to an appropriate virtual machine (Vm) and achieves a trade-off between cost and makespan while satisfying the deadline constraints. Rigorous examination of the algorithm is conducted on the various scale and cloud resources. The proposed algorithm is compared with Particle Swarm Optimization (PSO), Grey Wolf Optimizer(GWO), Bat Algorithm(BAT), and Genetic Algorithm(GA). Simulation results prove that it outperforms others by minimizing makespan, execution cost, Response time, and improving resource utilization throughput.
Subject
Decision Sciences (miscellaneous),Computational Mathematics,Computational Theory and Mathematics,Control and Optimization,Computer Science Applications,Modeling and Simulation,Statistics and Probability
Reference46 articles.
1. Improved multiobjective salp swarm optimization for virtual machine placement in cloud computing
2. Communication between individuals in salp chains II. physiology.;P. A.Anderson;Proceedings of the Royal Society of London. Series B, Biological Sciences,1980
3. A budget constrained scheduling algorithm for workflow applications.;H.Arabnejad;Journal of Grid Computing,2014
4. Enhanced Particle Swarm Optimization For Task Scheduling In Cloud Computing Environments;A. I.Awad;Procedia Computer Science,2015
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献