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Titlebook: Advances on Broad-Band Wireless Computing, Communication and Applications; Proceedings of the 1 Leonard Barolli,Makoto Takizawa,Keita Matsu

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樓主: eternal
61#
發(fā)表于 2025-4-1 02:49:49 | 只看該作者
DTN Routing Protocol Using Reinforcement Learning,meters for routing. The DTN routing protocol is designed to improve the delivery ratio of a message to its destination. Therefore, we consider several parameters that affect the message delivery ratio. In this paper, we propose a DTN routing protocol that uses reinforcement learning considering mult
62#
發(fā)表于 2025-4-1 08:50:04 | 只看該作者
63#
發(fā)表于 2025-4-1 13:46:10 | 只看該作者
https://doi.org/10.1057/9781137291837 theoretical probability that all packets are successfully delivered to the server with the basic redundant transmission scheme in a limited cycle period; and show its benefit through numerical results. This extension significantly increases the applicability of our optimal scheduling scheme.
64#
發(fā)表于 2025-4-1 18:03:29 | 只看該作者
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