Abstarct: In recent years, with the ever-growing demand for new clients and the integration of new customers into the world of computing, computing systems need to change and become more powerful and flexible than before. Cloud computing has emerged as a model beyond a system that is now capable of responding to most applications such as data storage, increased data security, access to the latest personal documents, software and hardware usage, and more. . One of the techniques needed to increase the flexibility and scalability of cloud data centers is migration. Migration is accomplished with a variety of purposes including load balancing, fault tolerance, power management, reduced response time and improved service quality, server's maintenance. The main purpose of this research is scheduling tasks and load balancing in cloud environment using ant colony algorithm. Load balancing is a challenging problem in cloud environment. Load balancing is a distribution process in which load is distributed across different nodes of the system to make better use of resources. The ant is used to maintain the load balance in the node so we can avoid overloading, idle or underloaded nodes. The proposed method has three main phases. The first phase is finding overloaded physical machines, the second phase is finding virtual machines with the shortest migration time, and the third phase is the virtual machine migration operations. Implementation has improved resource efficiency. The simulation results are presented in this thesis.