Load balancing techniques in cloud computing can be applied at different levels. There are two main levels: load balancing on physical server and load balancing on virtual servers. Load balancing on a physical server is policy of allocating physical servers to virtual machines. And load balancing on virtual machines is a policy of allocating resources from physical server to virtual machines for tasks or applications running on them. Depending on the requests of the user on cloud computing is SaaS (Software as a Service), PaaS (Platform as a Service) or IaaS (Infrastructure as a Service) that has a proper load balancing policy. When receiving the task, the cloud data center will have to allocate these tasks efficiently so that the response time is minimized to avoid congestion. Load balancing should also be performed between different datacenters in the cloud to ensure minimum transfer time. In this paper, we propose a virtual machine-level load balancing algorithm that aims to improve the average response time and average processing time of the system in the cloud environment. The proposed algorithm is compared to the algorithms of Avoid Deadlocks [5], Maxmin [6], Throttled [8] and the results show that our algorithms have optimized response times.