Tootfinder

Reliable Transmission of LTP Using Reinforcement Learning-Based Adaptive FEC
Liang Chen, Yu Song, Kanglian Zhao, Juan A. Fraire, Wenfeng Li
https://arxiv.org/abs/2506.22470

Reliable Transmission of LTP Using Reinforcement Learning-Based Adaptive FEC
Delay/Disruption Tolerant Networking (DTN) employs the Licklider Transmission Protocol (LTP) with Automatic Repeat reQuest (ARQ) for reliable data delivery in challenging interplanetary networks. While previous studies have integrated packet-level Forward Erasure Correction (FEC) into LTP to reduce retransmission time costs, existing static and delay-feedback-based dynamic coding methods struggle with highly variable and unpredictable deep space channel conditions. This paper proposes a reinfor…

Resilient Communication For Avalanche Response in Infrastructure-Limited Environments
Joshua Goulton, Milena Radenkovic
https://arxiv.org/abs/2506.22148 ht…

Resilient Communication For Avalanche Response in Infrastructure-Limited Environments
Delay Tolerant Networks (DTNs) offer a promising paradigm for maintaining communication in infrastructure limited environments, such as those encountered during natural disasters. This paper investigates the viability of leveraging an existing national transport system - the Swiss rail network - as a data mule backbone for disseminating critical avalanche alerts. Using The Opportunistic Network Environment (ONE) simulator, we model the entire Swiss rail network and conduct a rigorous comparativ…

Emerging Networks and Services in Developing Nations -- Barbados Use Case
Warren Scantlebury, Milena Radenkovic
https://arxiv.org/abs/2506.13934 https://…

Emerging Networks and Services in Developing Nations -- Barbados Use Case
This report aims to conduct an in-depth comparison of DTN (Delay/Disconnection Tolerant Network) performance and characteristics in the developing country of Barbados versus two major UK cities Nottingham and London. We aim to detect any common patterns or deviations between the two region areas and use the results of our network simulations to draw well-founded conclusions on the reasons for these similarities and differences. In the end we hope to be able to assimilate specific portions of th…