A GNN-based DRL model with two actor-critics produces comparable Pareto fronts for multi-objective fog application placement in milliseconds versus hours for genetic algorithms.
In: 2021 IEEE 12th International Confer- ence on Software Engineering and Service Science (ICSESS), pp
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Multi-objective application placement in fog computing using graph neural network-based reinforcement learning
A GNN-based DRL model with two actor-critics produces comparable Pareto fronts for multi-objective fog application placement in milliseconds versus hours for genetic algorithms.