Dec 28, 2020 · In CCR-RL, the task offloading decision is made considering data arrival rate, edge device computation power, and underlying transmission ...

In CCR-RL, the task offloading decision is made considering data arrival rate, edge device computation power, and underlying transmission capacity. Then, a deep ...

The simulation results demonstrate that the proposed method can achieve a minimal latency and a reduced processing cost compared to the state-of-the-art schemes ...

The simulation results demonstrate that the proposed method can achieve a minimal latency and a reduced processing cost compared to the state-of-the-art schemes ...

Apr 25, 2024 · Resource Offload Consolidation Based on Deep-Reinforcement Learning Approach in Cyber-Physical Systems. IEEE Trans. Emerg. Top. Comput ...

Aug 25, 2023 · This article provides a systematic review of the widely used RL approaches in computation offloading. It covers research in complementary paradigms.

The suggested FRLTO efficiently reduces energy consumption and latency while enhancing throughput and total WBAN utilization.

This article provides a systematic review of the widely used RL approaches in computation offloading. It covers research in complementary paradigms.

Rathore, A blockchain-based deep learning approach ... Mekala, Resource offload consolidation based on deep-reinforcement learning approach in cyber-physical ...

We then propose an improved deep Q-network (DQN) based service placement (DSP) algorithm. The proposed algorithm can achieve an optimal resource allocation by ...