An efficient scheme for in-orbit remote sensing image data retrieval

The conflict between real-time retrieval of remote sensing image data (RSID) and the limited satellite network transmission resources is becoming more and more prominent. To address it, this paper proposes a novel scheme for RSID retrieval from the remote sensing satellite network, which exploits the spatio-temporal characterization (STC) of sensing images to improve data retrieval efficiency. In particular, based on the spatio-temporal characterization, a data content naming scheme is introduced and an algorithm is accordingly proposed for RSID segmentation in satellite nodes. With the naming scheme, RSID retrieval can be implemented by making use of the Named Data Networking (NDN) architecture. The study aims to investigate the effectiveness of making use of the STC of RSID for the retrieval under the NDN architecture. To the best of our knowledge, this paper is the first to exploit STC to establish connections between user demands, RSID, and data naming for NDN. As a result, the proposed scheme makes the network aware of RSID's STC and consequently improves the data retrieval performance of the satellite network using NDN. The evaluation results show that the proposed scheme delivers about 65% and 7% higher retrieval hit rates than a retrieval scheme based on the original NDN proposal and a recently proposed scheme - CAP, respectively. In addition, comparing with these two schemes, the proposed one reduces transmission latency by about 20% and 15%, and traffic load by about 48% and 40%, all respectively. These imply that the proposed scheme outperforms in terms of higher data retrieval efficiency and better link utilization.& COPY; 2023 Elsevier B.V. All rights reserved.