Learning Selective Merge Policies for Deadline-Constrained Coded Caching via Deep Reinforcement Learning
In the coded caching, the server uses the cached information at the users to serve multiple users in parallel with a single coded multi-casting message or packet, that is, a merged packet, and thus mitigates the peak network congestion. In order to deliver the timely messages to the users in the deadline-driven applications like the video streaming, we must determine online the messages to be merged for the delivery, as there is a time limit for each request. It is important to note that while the merging aids the current coded multi-casting packet, it could harm the future deliveries. Our solution employs the deep reinforcement learning to view the coded multi-casting delivery as a maske...
| Authors | Amirhossein Yousefiramandi |
|---|---|
| Primary category | cs.IT |
| Published | 13 May 2026 |
| Last updated at source | 22 May 2026 |
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