• A Daniel
• Dr.N.Krishnaraj

As the world is advancing towards progressively proficient computing and quicker methodologies, cloud computing is a well known computing model to such expanding necessities. So as to give financially executions in cloud condition, task scheduling process is highly crucial. This paper proposes a method by combining the genetic algorithm (GA) and the particle swarm optimization (PSO) algorithm to improve load balancing and cloud throughput. We assess the results utilizing the CloudSim toolbox and reproduction results exhibit that the proposed methodology has a superior act regarding makespan, improvement proportion, and so on

Task scheduling; Particle swarm optimization; Genetic algorithm; Cloud computing

"TASK SCHEDULING MECHANISM FOR CLOUD COMPUTING USING HYBRID PARTICLE SWARM OPTIMIZATION ALGORITHM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.12-21, May - 2019, Available :http://www.jetir.org/papers/JETIRCN06004.pdf

"TASK SCHEDULING MECHANISM FOR CLOUD COMPUTING USING HYBRID PARTICLE SWARM OPTIMIZATION ALGORITHM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp12-21, May - 2019, Available at : http://www.jetir.org/papers/JETIRCN06004.pdf