Modeling and Simulation of 5G-based Edge Networks for Lightweight Machine Learning Applications.

Edge networking is poised to have a major impact in a number of fields, applications and services. In order to facilitate this, more advanced simulation will be necessary to model modern networked communication standards and develop edge computing frameworks which can take full advantage of the network's capabilities. PureEdgeSim is one such simulation system, which supports a high degree of modularity and extensibility. One extension is proposed and implemented here to add support to PureEdgeSim for 5G communication, based on parameter tuning derived from the technical specifications of 5G communication. The proposed extension of 5G communication is compared to the base with regards to task success rate, energy consumption, and network usage, and offers a difference in simulated performance consistent with expected 5G computing implementations. We used a lightweight machine earning applications like workload for experiments.