Abstract
Satellite communication is regarded as a promising technique for providing connectivity in remote areas, which creates opportunities for data collection and transmission in marine Internet-of-Remote-Things (IoRT) networks. Most existing investigations in the field of satellite access control focus on communication throughput and transmission delay. However, the freshness of information and the heterogeneous satellite networks are rarely considered. To this end, we first present a satellite-based marine IoRT system, where a GEO/LEO heterogeneous network is considered to harness the full potential of existing satellite systems, and the age-of-information (AoI) is introduced to characterize the freshness of the status update information generated by IoRT devices. Then, an optimal age-oriented access control problem is formulated to maintain the freshness of information in the long term. We transform this non-convex sequential decision problem into a model-free Markov Decision Process (MDP) problem and solve it by leveraging the deep reinforcement learning (DRL) framework. Simulation results show that the proposed strategy significantly outperforms the state-of-the-art ones in terms of long-term AoI performance. Moreover, the proposed strategy could make cooperative access decisions and obtain an excellent trade-off between satellites on different layers.
| Original language | English |
|---|---|
| Pages (from-to) | 662-667 |
| Number of pages | 6 |
| Journal | Proceedings - IEEE Global Communications Conference, GLOBECOM |
| DOIs | |
| State | Published - 2022 |
| Externally published | Yes |
| Event | 2022 IEEE Global Communications Conference, GLOBECOM 2022 - Rio de Janeiro, Brazil Duration: 4 Dec 2022 → 8 Dec 2022 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 14 Life Below Water
Keywords
- Internet of Remote Things (IoRT)
- age of information (AoI)
- deep reinforcement learning (DRL)
- heterogeneous satellite network
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