An adaptive end‐to‐end RTO calculation framework for DTNs with scheduled connectivity

In this work, we propose an end‐to‐end retransmission framework for dynamically calculating efficient retransmission time‐out intervals in delay‐tolerant networks (DTNs) with scheduled connectivity. The proposed framework combines deterministic and statistical information about the network state to calculate worst‐case estimates about the expected round trip times. Such information includes connectivity schedules, convergence layer protocols specifics, communication link characteristics, and network statistics about the maximum expected packet error rates and storage congestion. We detail the implementation of the proposed framework within the end‐to‐end application data conditioning layer proposed for the DTN architecture, realized by the Delay‐Tolerant Payload Conditioning protocol, as part of the Interplanetary Overlay Network–DTN reference implementation, and evaluate its performance in a complex deep‐space emulation scenario in our DTN testbed. Our results show that our approach achieves great accuracy in round‐trip time estimations and, therefore, faster retransmissions of lost data, in comparison to the statically configured retransmission mechanism of the original Delay‐Tolerant Payload Conditioning protocol. As a result, in‐order data reception rate and storage requirements on the receiver side are significantly improved, at minimum or even zero extra cost in transmission overhead due to duplicate transmissions.