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.
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A Realistic Mobile Edge Computing environment; with conditions for deadline and energy Energy-Constrained
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ImanRHT/MEC_Environment
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A Realistic Mobile Edge Computing environment; with conditions for deadline and energy Energy-Constrained
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