JIT_V3_N4_RP4 Rupavathy N. M. Mahil M.S. Mumtaj Zareena Journal on Information Technology 2277-5250 3 4 32 38 Cloud Computing, Resource Provisioning, Resource Scheduling, Particle Swarm Optimization, Workflow The initiation of resource provisioning in cloud computing for workflow scheduling. Most demanding issues in Clouds is Workflow Scheduling. However, Clouds are different from Grids in few ways: on-demand resource provisioning, homogeneous networks and the pay-as-you-go pricing model. We are proposing resource provisioning and scheduling strategy for scientific workflows using meta-heuristic optimization algorithm known as Particle Swarm Optimization. It aims is to minimize the overall execution cost while meeting timeframe constraints in various scientific workflows of different sizes. The results have been evaluated using Cloudsim with different QoS parameters which are user defined. The approach performs better than the genetic and ant colony optimization algorithms. September - November 2014 Copyright © 2014 i-manager publications. All rights reserved. i-manager Publications http://www.imanagerpublications.com/Article.aspx?ArticleId=3093