Performance analysis and functionality testing are major parts of developing distributed software systems. Since the number of communicating software instances heavily influences the behavior of distributed applications and communication protocols, evaluation scenarios have to consider a large number of nodes. Network emulation provides an infrastructure for running these experiments using real prototype implementations in a controllable and realistic environment. Large-scale experiments, however, have a high resource consumption which often exceeds available physical testbed resources. Time dilation allows for reducing the resource demands of a scenario at the expense of the experiment's runtime. However, current approaches only consider a constant time dilation factor, which wastes a lot of resources in case of scenarios with varying load.

We propose a framework for adaptive time virtualization that significantly reduces the runtime of experiments by improving resource utilization in network emulation testbeds. In this framework, resource demands are monitored and the time dilation factor is dynamically adapted to the required level. Our evaluation shows that adaptive virtual time in combination with our lightweight node virtualization architecture allows us to increase the possible scenario sizes by more than an order of magnitude and, at the same time, ensure unbiased emulation results. This represents an important contribution to making network emulation systems highly scalable.