The rapid expansion of the Internet has made understanding its intricate connections difficult. Hence, advanced techniques are needed to understand the underlying network. This thesis introduces a novel way to address the issue of visualizing the large-scale topology of the Internet. The proposed Inner Sphere visualization method projects the network topology on the inside of a sphere. User navigation around the network is accomplished through moving the sphere around the user's point of view. This approach to the visualization of large-scale networks builds upon previous work in the visualization and navigation of large data sets. Since previous research has shown that the spatial cognition ability in humans greatly affects the usefulness of a user interface, two empirical experiments were performed that test the usefulness of viewing topologies from the inside of a sphere compared to a flat surface. The results of our study show that network navigation on a sphere is faster but can also be confusing. Our Inner Sphere visualization method is implemented in a new tool for interactive network visualization called GerbilSphere. GerbilSphere takes into account the results of many user studies in order to create a more intuitive user interface.