The ability to expand research frontiers through system deployment has been hindered by a lack of experimentation frameworks that can be used to safely and accurately evaluate new algorithms and network protocols at scale. This is particularly true for anonymous communication systems, which are generally understood to be among the most secure ways to communicate online, but are difficult to experiment with because (1) they are designed to be resistent to observation and (2) experiments must be crafted very carefully to ensure they do not endanger the systems' users. This project develops the Anonymous Communication Experimentation (ACE) framework, a novel open-source software platform that enables privacy researchers to better understand and experiment with anonymity systems. ACE supports the construction of large, realistic, and high fidelity simulations of anonymity networks. ACE allows researchers to run existing software on top of a virtualized network, allowing them to safely and accurately evaluate the effectiveness of new attacks and defenses, and experiment with new protocols and algorithms before they are deployed in live networks. This project aims to promote the development of new algorithms and techniques for more robust and private communication by providing a framework for development and testing. ACE significantly advances the state-of-the-art in network simulation by providing: (1) an application emulation component to facilitate the execution of language-agnostic processes in support of website fingerprinting and censorship circumvention research; (2) a lightweight network simulation component that allows dynamic changes in support of location- and network-aware anonymous communication; (3) an interposition component to hook together the emulated processes with the simulated network; (4) a deterministic simulated virtual kernel that emulates Linux system calls; and (5) parallel and distributed execution components to ensure that ACE is accessible to universities and research labs that lack large server infrastructure. We will also develop a user interface, a toolkit to model inputs and visualize outputs, and a data repository to share and archive results.