The growing trend in cloud computing is the combination of Big Data and Big Data analytics that has been driven with rapid evolution of data center technologies towards more cost-effective solutions. Existing system Cura, for provisioning cost-effective MapReduce services in acloud. First, Cura is designed to provide a cost-effective solution to efficiently handle MapReduce production workloads that have a significant amount of interactive jobs. Second, unlike existing services that require customers to decide the resources to be used for the jobs, Cura leveragesMapReduce profiling to automatically create the best cluster configuration for the jobs. While the existing models allow only a per-job resource optimization for the jobs, Cura implements a globally efficient resource allocation scheme that significantly reduces the resource usage cost in the cloud. Third, Cura leverages unique optimization opportunities when dealing with workloads that can withstand some slack.This project presents a cost-effective resource management framework called (IWD) Intelligent Waterdrop algorithm that aim to minimize the infrastructure cost in the datacentre. IWDis a new technique that was used to solve job shop scheduling problem in Cloud.The IWD may results into better performance than existing workflow scheduling algorithms.