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.

中文翻译：

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面向数据主题的卫星观测数据传输调度算法

地球观测卫星（EOS）数据传输的调度是一个复杂的组合优化问题。随着遥感应用的发展，出现了一种新的特殊要求，即针对主题的数据传输。假设卫星从每次观测活动获得的数据都属于某些观测数据主题，并且每个观测数据主题都具有完整性和及时性要求。除非所有属于一个主题的观测数据都已在预期时间之前传输到地面，否则观测数据的值将急剧衰减，并且只有一部分数据传输的奖励（甚至没有奖励）会被消除。获得。当前的研究不能很好地满足新的数据主题传输要求。根据问题的特点，建立了数学调度模型，提出了一种基于进化计算的混合调度算法。为了进一步提高算法的性能并加快算法的收敛速度，设计了一种基于域知识的变异算子。定量实验结果表明，与现有技术相比，该算法更有效地解决了卫星观测数据主题的传输调度问题。