Ant Colony Optimization (ACO) is a machine learning technique first proposed by Colorni, Dorigo, and Maniezzo. It is modeled after a decentralized agent-based communication system, known as stigmergy, which is used by ant colonies to find the shortest distance between two points. This research investigates the application of a distributed ant routing algorithm (DARA) on a distributed network simulator (DOONS). DARA is a distributed agent-based ACO routing algorithm that builds on previous ACO concepts. DOONS was created as an easily modifiable Java based packet switching network simulator that runs on a local area network. Empirical results are given that show that the algorithm is successful at performing load balancing under a dynamic network environment.