An Efficient Real-time Scheduling and Proactive Data Download Algorithm for Earth Observation Satellites

Teng, Ling; Liu, Lixiang; Zheng, Changwen; Liang, Zhipeng

doi:10.1109/iscit.2018.8588009

Cited by 4 publications

(2 citation statements)

References 14 publications

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“…To verify the effectiveness of the HPG4TTalgorithm proposed by this paper, we compare it with three heuristic algorithms: first finished first service (F3S) [8], real-time scheduling and proactive data download algorithm (RSPD2) [14], and route reduction-based dynamic programming (R2DP) [16], as well as with three nature-inspired metaheuristic algorithms: simulated annealing algorithm for ground station scheduling (SAA4GS) [20], quantum discrete particle swarm optimization for data transmission (QPSO4DT) [2], and hybrid genetic algorithm combined with neighborhood search for data transmission (HGANS) [26].…”

Section: Baselinesmentioning

confidence: 99%

“…Liang et al [13] proposed a greedy strategybased heuristic data download scheduling algorithm which considered trade-offs among throughput, Qosand fairness. Ling et al [14] calculated the priority value of each data download task and then adopted a resource competition algorithm, which can be considered a ranking problem to select a data download task with high priority. Xiao et al [15] modeled the multisatellite observation and datadownlink scheduling problem as a two-stage flow shop scheme.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Satellite Observation Data Transmission Scheduling Algorithm Oriented to Data Topics

Chen

Zhai

et al. 2020

International Journal of Aerospace Engineering

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The scheduling of Earth Observation Satellite (EOS) data transmission is a complex combinatorial optimization problem. With the development of remote sensing applications, a new special requirement named data transmission oriented to topics has appeared. It supposes that the data obtained from each observation activity by satellites belong to certain observation data topics, and every observation data topic has completeness and timeliness requirements. Unless all of the observation data belonging to one topic has been transmitted to the ground before the expected time, the value of the observation data will be decayed sharply and only a part of the rewards (or even no reward) for the data transmission will be obtained. Current researches do not meet the new data topic transmission requirements well. Based on the characteristics of the problem, a mathematic scheduling model is established, and a novel hybrid scheduling algorithm based on evolutionary computation is proposed. In order to further enhance the performance and speed up the convergence process of our algorithm, a domain-knowledge-based mutation operator is designed. Quantitative experimental results show that the proposed algorithm is more effective to solve the satellite observation data topic transmission scheduling problem than that of the state-of-the-art approaches.

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