The Tor anonymous communication network and Bitcoin financial transaction network are examples of security applications with significant risk to user privacy if they fail to perform as expected. Experimentation on private instances of these networks is therefore a popular means to design, develop, and test improvements before deploying them to real users. In particular, the Shadow discrete-event network simulator is one of the most popular tools for conducting safe and ethical Tor research. In this paper, we analyze Shadow’s design and find significant performance bottlenecks in its logging and work scheduling systems stemming from its representation of simulated processes and its use of a globally shared process namespace. We design, implement, and empirically evaluate new algorithms that replace each of these components. We find that our improvements reduce Shadow run time by as much as 31% in synthetic benchmarks over a variety of conditions, and by as much as 73% over small and large experimental Tor networks. Our improvements have been merged into Shadow release v1.12.0 to the benefit of the security and privacy communities.