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- W2911125611 abstract "Given decoupling the control layer and the infrastructure layer, the software-defined wireless networks (SDWNs) is beneficial in terms of providing both low-latency and low-energy consumption services for mobile users, where multi-controller placement and resource management become a pair of bottlenecks. In this letter, we propose an energy-aware multi-controller placement scheme as well as a latency-aware resource management model for the SDWN. Moreover, the particle swarm optimization is invoked for solving the multi-controller placement problem, and a deep reinforcement learning algorithm-aided resource allocation strategy is conceived. Finally, experimental results show that our proposed schemes are conducive to reducing both the execution time and the energy consumption of each task." @default.
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- W2911125611 date "2019-03-01" @default.
- W2911125611 modified "2023-10-18" @default.
- W2911125611 title "Multi-Controller Resource Management for Software-Defined Wireless Networks" @default.
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- W2911125611 doi "https://doi.org/10.1109/lcomm.2019.2891527" @default.
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