Abstract
The enormous amount of network equipment and users implies a tremendous growth of Internet traffic for multi-media services. To mitigate the traffic pressure, architectures with in-network storage have been proposed to cache popular content at devices in close proximity to users in order to decrease the number of backhaul hops. Meanwhile, the reduced transmission distance also contributes to energy saving. However, due to limited storage, only a fraction of the content can be cached, while caching the most popular content is cost-effective. Correspondingly, it becomes essential to devise an effective popularity prediction method. In this regard, some existing efforts manifest the effectiveness of dynamic graph neural network (DGNN) models, but it remains challenging to tackle sparse datasets. Herein, we first propose a reformative temporal graph network, named STGN, to address the challenge and improve prediction performance. Specifically, the STGN model leverages extra semantic messages to help establish implicit paths within the sparse interaction graph and enhance the temporal and structural learning of a DGNN model. Furthermore, we devise a user-specific attention mechanism to aggregate various semantics in a fine-grained manner. Finally, extensive simulations verify the superiority of our STGN models and demonstrate the potential in terms of energy-saving.
Original language | English |
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Title of host publication | ICC 2023 - IEEE International Conference on Communications |
Subtitle of host publication | Sustainable Communications for Renaissance |
Editors | Michele Zorzi, Meixia Tao, Walid Saad |
Publisher | IEEE Institute of Electrical and Electronic Engineers |
Pages | 1724-1729 |
Number of pages | 6 |
ISBN (Electronic) | 9781538674628 |
DOIs | |
Publication status | Published - 2023 |
MoE publication type | A4 Article in a conference publication |
Event | 2023 IEEE International Conference on Communications, ICC 2023 - Rome, Italy Duration: 28 May 2023 → 1 Jun 2023 |
Conference
Conference | 2023 IEEE International Conference on Communications, ICC 2023 |
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Country/Territory | Italy |
City | Rome |
Period | 28/05/23 → 1/06/23 |
Keywords
- Content caching
- dynamic graph neural network
- energy saving
- popularity prediction
- semantics