Multi-satellite data downlink resource scheduling algorithm for incremental observation tasks based on evolutionary computation

Chen, Hao; Zhong, Zhinong; Wu, Jiangjiang; Jing, Ning

doi:10.1109/icaci.2015.7184787

Cited by 12 publications

(4 citation statements)

References 9 publications

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“…The basic idea of this method is that once the algorithm stops, the distribution of the pheromone trajectory can be changed by updating the pheromone trajectory with the guided solution. When the number of satellite observation task requests increases over time, the multi-satellite data downlink resource scheduling cannot be handled effectively [33]. One paper refers to a data downlink resource scheduling model that adapts to the observation task increment that is established to solve this problem.…”

Section: Resource Scheduling Methods Based On An Intelligent Optimiza...mentioning

confidence: 99%

An Efficient Satellite Resource Cooperative Scheduling Method on Spatial Information Networks

Fan

Yang

et al. 2021

Mathematics

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To overcome the low timeliness of resource scheduling problems in spatial information networks, we propose a method based on a dynamic reconstruction of resource request queues and the autonomous coordinated scheduling of resources. First, we construct a small satellite network and combine the graph maximum flow theory to solve the link resource planning problem during inter-satellite data transmission. In addition, we design a multi-satellite resource scheduling algorithm with minimal time consumption based on graph theory. The algorithm is based on graph theory to reallocate the resource request queue to satellites with idle processing resources. Finally, we simulate the efficient resource scheduling capability in the spatial information network and empirically compare our approaches against two representative swarm intelligence baseline approaches and show that our approach has significant advantages in terms of performance and time consumption during resource scheduling.

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Section: Resource Scheduling Methods Based On An Intelligent Optimiza...mentioning

confidence: 99%

An Efficient Satellite Resource Cooperative Scheduling Method on Spatial Information Networks

Fan

Yang

et al. 2021

Mathematics

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“…Tsatsoulis and van Dyne [23] introduced some artificial intelligence techniques, including case-based reasoning, rule-based systems, and generate-and-test techniques into the scheduling problem of the AFSCN (Air Force Satellite Control Network) [6]. Chen et al [2,24,25] employed improved genetic algorithm and particle swarm optimization algorithm to handle the satellite data transmission scheduling problem with some specific requirements, for incremental observation tasks, member satellites of the same cluster, and real-time and playback data transmission modes. Addressing the satellite image downlink scheduling problem, Yao et al [26] and Song et al [27] brought up a heuristic genetic algorithm.…”

Section: Introductionmentioning

confidence: 99%

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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“…Aiming at these problems, they designed heuristic algorithms and GA [14]. Chen et al used a resource scheduling model that considers task increments to solve the multisatellite data downlink resource scheduling problem through an evolutionary calculation method [15]. Chu et al constructed a satellite mission scheduling model with time-dependent constraints and proposed a branch-and-bound algorithm to solve this problem accurately [16].…”

Section: Introductionmentioning

confidence: 99%

A Heuristic Genetic Algorithm for Regional Targets’ Small Satellite Image Downlink Scheduling Problem

Song

Zhang

Sun

et al. 2019

International Journal of Aerospace Engineering

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Small satellite image downlink scheduling problem (SSIDSP) is an important part of satellite mission planning. SSIDSP mainly needs to balance how to better match the limited receiving capacity of the ground station with the limited satellite resources. In this paper, regional targets are considered with SSIDSP. We propose a mathematical model that maximizes profit by considering time value and regional targets. A downlink schedule algorithm (DSA) is proposed to complete the task sequence arrangement and generate scheduling results. A heuristic genetic algorithm (HGA) is used to optimize the generated task sequence to achieve higher profit. Three scale test instances are used to test the effectiveness of HGA and DSA. We compare the effect of HGA, basic genetic algorithm (GA), and construction heuristic algorithm. The experimental results proved that the proposed approach ensures the successful completion of observation tasks and is effective for SSIDSP.

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Multi-satellite data downlink resource scheduling algorithm for incremental observation tasks based on evolutionary computation

Cited by 12 publications

References 9 publications

An Efficient Satellite Resource Cooperative Scheduling Method on Spatial Information Networks

An Efficient Satellite Resource Cooperative Scheduling Method on Spatial Information Networks

A Satellite Observation Data Transmission Scheduling Algorithm Oriented to Data Topics

A Heuristic Genetic Algorithm for Regional Targets’ Small Satellite Image Downlink Scheduling Problem

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