  So far, various solutions have been proposed for symmetric distribution of
load cloud computing environments. In this article, a new solution to the
optimal allocation of virtual machines in the cloud data centers is presented
to provide a good load balancing among servers. The proposed method offers a
solution uses learning automata as a reinforcement learning model to improve
the performance of the optimization algorithm for optimal placement of virtual
machines. Also, it helps the search algorithm to converge more quickly to the
global optimum. The simulation results show the proposed method has been able
to perform good level of load balancing in cloud data centers.
