This thesis studies the area of virtualization. The focus is on the sub-area live migration, a technique that allows a seamless migration of a virtual machine from one physical machine to another physical machine. Virtualization is an attractive technique, utilized in large computer systems, for example data centers. By using live migration, data center administrators can migrate virtual machines, seamlessly, without the users of the virtual machines taking notice about the migrations. Manually initiated migrations can become cumbersome, with an ever-increasing number of physical machines. The number of physical and virtual machines is not the only problem, deciding when to migrate and where to migrate are other problems that needs to be solved. Manually initiated migrations can also be inaccurate and untimely. Two different strategies for automated live migration have been developed in this thesis. The Push and the Pull strategies. The Push strategy tries to get rid of virtual machines and the Pull strategy tries to steal virtual machines. Both of these strategies, their design and implementation, are presented in the thesis. The strategies utilizes Shannon's Information Entropy to measure the balance in the system. The strategies further utilizes a cost model to predict the time a migration would require. This is used together with the Information Entropy to decide which virtual machine to migrate if and when a hotspot occurs. The implementation was done with the help of OMNeT++, an open-source simulation tool. The strategies are evaluated with the help of a set of simulations. These simulations include a variety of scenarios with different workloads. Our results shows that the developed strategies can re-balance a system of computers, after a large amount of virtual machines has been added or removed, in only 4-5 minutes. The results further shows that our strategies are able to keep the system balanced when the system load is at medium. This while virtual machines are continuously added or removed from the system. The contribution this thesis brings to the field is a model for how automated live migration of virtual machines can be done to improve the performance of a computer system, for example a data center.