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Cloud computing is a technique proposed based on the distribution of processing and storage resources across various multiple servers. The user can easily access the services and applications of cloud at any location and moment in this infrastructure. Although these capabilities have made the cloud services more flexible and available, issues such as scheduling and load balancing for optimal use of resources, have always been the main challenges in this infrastructure. The load balancing and scheduling significantly increase the possibility of using resources and provide the grounds for fault tolerance. Even if the intended node is under the low or high loading, the load balancing techniqu es can increase its efficiency. In this paper, a scheduling technique is presented for optimal resource allocation with the enhanced particle swarm optimization, and virtual machine live migration technique. Through this solution, while reducing the execution time, grounds are provided to reduce energy consumption in the cloud environment.