Abstract
Cloud computing is designed such a way to avoid over-provisioning when used with utility pricing. It also removes the need to over-provision in order to meet the demands of users. It involves multitenancy and multitasks, i.e., many customers can perform different tasks, accessing a single or multiple application instances. Sharing resources among a large pool of users assists in reducing infrastructure costs and peak load capacity. Due to the raise in convention of many applications currently, there is necessitating for high processing and storage capacity along with the consideration of cost and instance use. To provide proficient resources, Cloud computing is been pioneered. Many organizations have their own private cloud, but when there is need for extra resources they go for public cloud where they have been outlaid for their use. In such “pay-per-use”, workflow execution cost must be considered during scheduling based on users' QoS constraints. It is an algorithm that calculates an optimal value and instance for it. Using simulation, we have compared the performance of our proposed approach with the existing scheduling strategies for different type and size of workflows. The IVH algorithm comes to the decision of desiring which resource should be chartered from public providers.
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