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Resource allocation and pricing techniques in cloud computing is a challenging task for every researcher. Everyone try to find out a good solutions of resource allocation and pricing in a dynamic way. Every user give their demands for taking the cloud resources for a particular time period. If the request is not fulfilled within the time period then the user ask for extra time for completion his task. The cloud computing automatically generate a reverse auction strategy for implementing the task and the task will be performed in the other cloud which have been participated in the auction. Here we have proposed Resource Allocation with Economical Strategy (RAES) as an efficient and cost-effective framework for resource allocation with pricing . We have compared our algorithm with ECON and Greedy algorithm. For simulation purpose, we keep number of users and capacity of the system constant and vary average number of CPU required by the users. We observe that number of allocations made by our algorithm is significantly good perform than the basic ECON scheduling algorithm and Greedy algorithm