• ishadeep kaur
• P S Mann

Abstract : Cloud Computing is emerging as a new paradigm that provides high quality and low-cost information services by pay-per-use model, but still it has several issues that need to be focused to execute scientific workflows. Workflow scheduling is one of the critical issue in cloud computing which aims to find a feasible schedule that minimizes the finish time and execution cost while meeting the quality of service requirements .Efficient scheduling can have significant impact on the performance of the system. In this paper, we propose a hybrid cost effective Genetic and Firefly Algorithm for workflow scheduling in cloud computing. In existing approach the number of iterations are very large which increases the Total Execution Cost and Total Execution Time which we will optimize in proposed algorithm. The initial population is generated by the PEFT algorithm which makes the use of OCT table is fed to hybrid algorithm of Firefly algorithm and Genetic Algorithm. The best optimized schedule is produced by the Hybrid of Genetic and Firefly Algorithm. The performance evaluation on well-known scientific workflows such as Montage, LIGO and Epigenomics of different size shows that our proposed hybrid algorithm performs better than the existing algorithm.

Cloud Computing, scientific workflows, Workflow scheduling, quality of service (QoS)

"A HYBRID COST EFFECTIVE ALGORITHM FOR WORKFLOW SCHEDULING IN CLOUD COMPUTING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.613-621, June-2019, Available :http://www.jetir.org/papers/JETIR1906377.pdf

"A HYBRID COST EFFECTIVE ALGORITHM FOR WORKFLOW SCHEDULING IN CLOUD COMPUTING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp613-621, June-2019, Available at : http://www.jetir.org/papers/JETIR1906377.pdf