A realistic simulation of resource-constrained, time-varying, distributed computing environments, designed for Deep Reinforcement Learning-based computation offloading algorithms in the Internet of Things, Edge, and Fog Computing domains. Key features include: Support for multi-user, multi-server systems; Compatibility with time-sensitive applications; Task processing with strict deadlines; and Dynamic distributed clustering.