Goal-Oriented Bundle Management and Flow Control for Deep-Space Communications via Reinforcement Learning
Deep-space communications operate under intermittent connectivity, long propagation delays, and relay storage constraints. In such networks, the Bundle Protocol enables store-carry-forward communication, requiring relay nodes to manage limited storage and scarce contact opportunities. Relay-side scheduling and dropping decisions are inherently goal-oriented: transmission resources should be allocated to bundles most valuable to downstream mission objectives. Conventional schedulers, such as FIFO, do not explicitly optimize task utility and may provide unfair service across heterogeneous planetary sources. This paper presents a closed-loop modeling and learning framework for relay-side bun...
| Authors | Sajjad Baghaee, Aimin Li, Shanmugarajan Balasubramanian et al. |
|---|---|
| Primary category | cs.NI |
| Published | 9 October 2026 |
| Last updated at source | 9 October 2026 |
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