We propose an intelligent policy to attain an equitable tradeoff between the average AoI and cache update cost, which is quantified as transmission energy ...

Deep Reinforcement Learning for loT Networks: Age of Information and Energy Cost Tradeoff. Abstract: In most Internet of Things (IoT) networks, edge nodes ...

Reinforcement Learning. Conference Paper. Deep Reinforcement Learning for IoT Networks: Age of Information and Energy Cost Tradeoff. December 2020. DOI:10.1109 ...

Apr 27, 2024 · To address this issue, we adopt the Age of Information (AoI) to quantify data freshness and propose an online cache update scheme to obtain an ...

Deep Reinforcement Learning for IoT Networks: Age of Information and Energy Cost Tradeoff. Authors: Author Picture Xiongwei Wu. The Chinese University of Hong ...

Mar 1, 2020 · Abstract—Caching has been regarded as a promising technique to alleviate energy consumption of sensors in Internet of Things. (IoT) networks by ...

Jul 1, 2022 · We demonstrate through simulations that, our proposed algorithm can achieve greatly smaller average weighted sum-AoI than the available DQN- ...

Abstract—In this paper, we study a real-time monitoring system in which multiple source nodes are responsible for sending.

In this paper, we propose the optimal power allocation to achieve it based on deep reinforcement learning (DRL). Simulations have demonstrated that the optimal ...

Jul 27, 2023 · In this paper, we study a real-time monitoring system in which distributed Internet of Things (IoT) devices are responsible for the sampling ...