Cloud computing is the latest technology and it gives excellent possibilities to solve a systematic difficulties. It provides many queries that is used to finish the work economically. Even though it offers many benefits in workflow applications it also has some threats in cloud circumstances. In the existing invention the work get neglected due to the user's Quality of Service (QoS) and also it combines elasticity and heterogeneity as basic principles in computing assets. This paper presents resource provisioning and scheduling strategy for systematic workflows on Infrastructure as a Service (IaaS) Cloud. We use two algorithms namely meta-heuristic optimization technique and Particle Swarm Optimization (PSO), which plans to reduce the workflow execution cost in deadline constraints. Our heuristic is evaluated using systematic workflows and CloudSim. The conclusion of our project is, it advances better than the current state-of-the-art algorithms.
R.Ramesh Kannan, S.Abinaya, D.Dheepikaraghavi
Cloud Computing, Systematic Workflow, Resource Provisioning, Scheduling
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