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Journal articles on the topic 'Satellite Scheduling'

Author: Grafiati

Published: 4 June 2021

Last updated: 13 February 2022

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1

Cui, Jintian, and Xin Zhang. "Application of a Multi-Satellite Dynamic Mission Scheduling Model Based on Mission Priority in Emergency Response." Sensors 19, no. 6 (March 23, 2019): 1430. http://dx.doi.org/10.3390/s19061430.

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Emergency observations are missions executed by Earth observation satellites to support urgent ground operations. Emergency observations become more important for meeting the requirements of highly dynamic and highly time-sensitive observation missions, such as disaster monitoring and early warning. Considering the complex scheduling problem of Earth observation satellites under emergency conditions, a multi-satellite dynamic mission scheduling model based on mission priority is proposed in this paper. A calculation model of mission priority is designed for emergency missions based on seven impact factors. In the satellite mission scheduling, the resource constraints of scheduling are analyzed in detail, and the optimization objective function is built to maximize the observation mission priority and mission revenues, and minimize the waiting time for missions that require urgency for execution time. Then, the hybrid genetic tabu search algorithm is used to obtain the initial satellite scheduling plan. In case of the dynamic arrival of new emergency missions before scheduling plan releases, a dynamic scheduling algorithm based on mission priority is proposed to solve the scheduling problem caused by newly arrived missions and to obtain the scheduling plan of newly arrived missions. A simulation experiment was conducted for different numbers of initial missions and newly arrived missions, and the scheduling results were evaluated with a model performance evaluation function. The results show that the execution probability of high-priority missions increased because the mission priority was taken into account in the model. In the case of more satellite resources, when new missions dynamically arrived, the satellite resources can be reasonably allocated to these missions based on the mission priority. Overall, this approach reduces the complexity of the dynamic adjustment and maintains the stability of the initial scheduling plan.

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Feng, Yao, Ren Jie He, Ju Fang Li, and Li Ning Xing. "Research on Joint Scheduling of Multiple Imaging Satellites with Multiple Sensors." Advanced Materials Research 186 (January 2011): 616–20. http://dx.doi.org/10.4028/www.scientific.net/amr.186.616.

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Guided by the application requirements of imaging satellite, this work focuses on the model construction and heuristic rule design to the joint scheduling problem of multi imaging satellites. It analyses the imaging procedure, imaging constraints, inputs and outputs, the basic scheduling flow and characteristics of the joint scheduling problem of multi imaging satellites. The heuristic algorithm was proposed to effectively solve this problem. Finally, a multi imaging satellites scheduling system is developed.

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3

Zhang, Shengyu, Zhencai Zhu, Haiying Hu, and Yuqing Li. "Research on Task Satellite Selection Method for Space Object Detection LEO Constellation Based on Observation Window Projection Analysis." Aerospace 8, no. 6 (May 31, 2021): 156. http://dx.doi.org/10.3390/aerospace8060156.

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Aiming at the task planning and scheduling problem of space object detection LEO constellation (SODLC) for detecting space objects in deep space background, a method of SODLC task satellite selection based on observation window projection analysis is proposed. This method projects the spatial relative relationships of the SODLC observation blind zone, observation range, and the initial spatial position of the objects onto the surface of the earth for detectable analysis of satellites and targets and binds the dynamic observation conditions to the satellite trajectory after projection calculation of the visible relationship between target changes. On this basis, combined with the features of SODLC with high orbital symmetry, the task satellite selection is divided into two steps: orbit plane selection and task satellite selection. The orbit planes are selected based on the longitude range of the ascending node with the geographic location of the targets, and the task satellites are selected according to the relative motion relationship between the satellites and the targets together with the constraints of observable conditions. The selection method simplifies the calculation process of scheduling and selecting task satellites. Simulation analysis prove the method has better task satellite selection efficiency. The method has high practical value for task planning and scheduling for event-driven SODLC.

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Li, H. J., Y. Lu, F. H. Dong, and R. Liu. "Communications Satellite Multi-Satellite Multi-Task Scheduling." Procedia Engineering 29 (2012): 3143–48. http://dx.doi.org/10.1016/j.proeng.2012.01.455.

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Niu, X. N., H. Tang, and L. X. Wu. "MULTI-SATELLITE OBSERVATION SCHEDULING FOR LARGE AREA DISASTER EMERGENCY RESPONSE." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3 (April 30, 2018): 1327–31. http://dx.doi.org/10.5194/isprs-archives-xlii-3-1327-2018.

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an optimal imaging plan, plays a key role in coordinating multiple satellites to monitor the disaster area. In the paper, to generate imaging plan dynamically according to the disaster relief, we propose a dynamic satellite task scheduling method for large area disaster response. First, an initial robust scheduling scheme is generated by a robust satellite scheduling model in which both the profit and the robustness of the schedule are simultaneously maximized. Then, we use a multi-objective optimization model to obtain a series of decomposing schemes. Based on the initial imaging plan, we propose a mixed optimizing algorithm named HA_NSGA-II to allocate the decomposing results thus to obtain an adjusted imaging schedule. A real disaster scenario, i.e., 2008 Wenchuan earthquake, is revisited in terms of rapid response using satellite resources and used to evaluate the performance of the proposed method with state-of-the-art approaches. We conclude that our satellite scheduling model can optimize the usage of satellite resources so as to obtain images in disaster response in a more timely and efficient manner.

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Feng, Yao, Ren Jie He, Ju Fang Li, and Li Ning Xing. "An Intelligent Approach to Dynamic Scheduling System of Earth Observation Satellites." Advanced Materials Research 186 (January 2011): 591–95. http://dx.doi.org/10.4028/www.scientific.net/amr.186.591.

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With the increased number of earth observation satellites, the process of acquiring high quality solution schedule for multi-satellite, multi-orbit and multi-user is more difficult than before. The multi-objective hierarchical genetic algorithm with preference and dynamic heuristic algorithm are proposed to solve the dynamic scheduling problem of earth observation satellite system. The experimental results performed on some benchmark problems suggest that this proposed approach is effective to the dynamic scheduling system.

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7

Li, Yu Qing, Ri Xin Wang, and Min Qiang Xu. "An Evolution Algorithm for Satellite Range Scheduling Problem with Priority Constraint." Applied Mechanics and Materials 568-570 (June 2014): 775–80. http://dx.doi.org/10.4028/www.scientific.net/amm.568-570.775.

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The satellite range scheduling problem is one of the most important problems in the field of the satellite operation. The purpose of this problem is finding the optimal feasible schedules, scheduling the communications between satellites and ground stations effectively, in another word. The problem is known for its high complexity and is an over-constrained problem. This paper present the resolution of the problem through a Station Coding Based Evolution Algorithm, particularly with the priority constraint, which adopting a new chromosome encoding method based on arranging the tasks in the ground station ID order. Computational results and analysis are presented for the case of the multi-ground stations scheduling.

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Li, Jiang Cheng, Li Ning Xing, Ying Wu Chen, and Xiang Yu Wei. "Electronic Satellite Scheduling Problem and its Heuristic Method." Advanced Materials Research 989-994 (July 2014): 4062–68. http://dx.doi.org/10.4028/www.scientific.net/amr.989-994.4062.

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The problem of scheduling for electronic satellites is a serious problem involving a lot of complex constraints. Considering the specific constraints of electromagnetic detection electronic satellite, on the basis of rational hypothesis, a multi-objective mathematic model was established. Several basic scheduling strategies were proposed. Based on the roulette method and hierarchical optimization method, a heuristic algorithm based on the rules was designed. A comprehensive evaluation with Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for the algorithm was offered. Finally, some experiments are conducted to verify the correctness and practicability of our scheduling model and algorithm.

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9

Chen, Hao, Shu Yang, Jun Li, and Ning Jing. "Exact and Heuristic Methods for Observing Task-Oriented Satellite Cluster Agent Team Formation." Mathematical Problems in Engineering 2018 (August 6, 2018): 1–23. http://dx.doi.org/10.1155/2018/2103625.

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With the development of aerospace science and technology, Earth Observation Satellite cluster which consists of heterogeneous satellites with many kinds of payloads appears gradually. Compared with the traditional satellite systems, satellite cluster has some particular characteristics, such as large-scale, heterogeneous satellite platforms, various payloads, and the capacity of performing all the observation tasks. How to select a subset from satellite cluster to perform all observation tasks effectively with low cost is a new challenge arousing in the field of aerospace resource scheduling. This is the agent team formation problem for observation task-oriented satellite cluster. A mathematical scheduling model is built. Three novel algorithms, i.e., complete search algorithm, heuristic search algorithm, and swarm intelligence optimization algorithm, are proposed to solve the problem in different scales. Finally, some experiments are conducted to validate the effectiveness and practicability of our algorithms.

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Zhuang, Shufeng, Zhendong Yin, Zhilu Wu, and Xiaoguang Chen. "Dynamic Relay Satellite Scheduling Based on ABC-TOPSIS Algorithm." Mathematical Problems in Engineering 2016 (2016): 1–11. http://dx.doi.org/10.1155/2016/3161069.

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Tracking and Data Relay Satellite System (TDRSS) is a space-based telemetry, tracking, and command system, which represents a research field of the international communication. The issue of the dynamic relay satellite scheduling, which focuses on assigning time resource to user tasks, has been an important concern in the TDRSS system. In this paper, the focus of study is on the dynamic relay satellite scheduling, whose detailed process consists of two steps: the initial relay satellite scheduling and the selection of dynamic scheduling schemes. To solve the dynamic scheduling problem, a new scheduling algorithm ABC-TOPSIS is proposed, which combines artificial bee colony (ABC) and technique for order preference by similarity to ideal solution (TOPSIS). The artificial bee colony algorithm is performed to solve the initial relay satellite scheduling. In addition, the technique for order preference by similarity to ideal solution is adopted for the selection of dynamic scheduling schemes. Plenty of simulation results are presented. The simulation results demonstrate that the proposed method provides better performance in solving the dynamic relay satellite scheduling problem in the TDRSS system.

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11

Niu, Xiaonan, Hong Tang, Lixin Wu, Run Deng, and Xuejun Zhai. "Imaging-Duration Embedded Dynamic Scheduling of Earth Observation Satellites for Emergent Events." Mathematical Problems in Engineering 2015 (2015): 1–31. http://dx.doi.org/10.1155/2015/731734.

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We present novel two-stage dynamic scheduling of earth observation satellites to provide emergency response by making full use of the duration of the imaging task execution. In the first stage, the multiobjective genetic algorithm NSGA-II is used to produce an optimal satellite imaging schedule schema, which is robust to dynamic adjustment as possible emergent events occur in the future. In the second stage, when certain emergent events do occur, a dynamic adjusting heuristic algorithm (CTM-DAHA) is applied to arrange new tasks into the robust imaging schedule. Different from the existing dynamic scheduling methods, the imaging duration is embedded in the two stages to make full use of current satellite resources. In the stage of robust satellite scheduling, total task execution time is used as a robust indicator to obtain a satellite schedule with less imaging time. In other words, more imaging time is preserved for future emergent events. In the stage of dynamic adjustment, a compact task merging strategy is applied to combine both of existing tasks and emergency tasks into a composite task with least imaging time. Simulated experiments indicate that the proposed method can produce a more robust and effective satellite imaging schedule.

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12

Xhafa, Fatos, Junzi Sun, Admir Barolli, Alexander Biberaj, and Leonard Barolli. "Genetic Algorithms for Satellite Scheduling Problems." Mobile Information Systems 8, no. 4 (2012): 351–77. http://dx.doi.org/10.1155/2012/717658.

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Recently there has been a growing interest in mission operations scheduling problem. The problem, in a variety of formulations, arises in management of satellite/space missions requiring efficient allocation of user requests to make possible the communication between operations teams and spacecraft systems. Not only large space agencies, such as ESA (European Space Agency) and NASA, but also smaller research institutions and universities can establish nowadays their satellite mission, and thus need intelligent systems to automate the allocation of ground station services to space missions. In this paper, we present some relevant formulations of the satellite scheduling viewed as a family of problems and identify various forms of optimization objectives. The main complexities, due highly constrained nature, windows accessibility and visibility, multi-objectives and conflicting objectives are examined. Then, we discuss the resolution of the problem through different heuristic methods. In particular, we focus on the version of ground station scheduling, for which we present computational results obtained with Genetic Algorithms using the STK simulation toolkit.

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Niu, X. N., X. J. Zhai, H. Tang, and L. X. Wu. "MULTI-SATELLITE SCHEDULING APPROACH FOR DYNAMIC AREAL TASKS TRIGGERED BY EMERGENT DISASTERS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B1 (June 3, 2016): 475–81. http://dx.doi.org/10.5194/isprsarchives-xli-b1-475-2016.

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The process of satellite mission scheduling, which plays a significant role in rapid response to emergent disasters, e.g. earthquake, is used to allocate the observation resources and execution time to a series of imaging tasks by maximizing one or more objectives while satisfying certain given constraints. In practice, the information obtained of disaster situation changes dynamically, which accordingly leads to the dynamic imaging requirement of users. We propose a satellite scheduling model to address dynamic imaging tasks triggered by emergent disasters. The goal of proposed model is to meet the emergency response requirements so as to make an imaging plan to acquire rapid and effective information of affected area. In the model, the reward of the schedule is maximized. To solve the model, we firstly present a dynamic segmenting algorithm to partition area targets. Then the dynamic heuristic algorithm embedding in a greedy criterion is designed to obtain the optimal solution. To evaluate the model, we conduct experimental simulations in the scene of Wenchuan Earthquake. The results show that the simulated imaging plan can schedule satellites to observe a wider scope of target area. We conclude that our satellite scheduling model can optimize the usage of satellite resources so as to obtain images in disaster response in a more timely and efficient manner.

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Niu, X. N., X. J. Zhai, H. Tang, and L. X. Wu. "MULTI-SATELLITE SCHEDULING APPROACH FOR DYNAMIC AREAL TASKS TRIGGERED BY EMERGENT DISASTERS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B1 (June 3, 2016): 475–81. http://dx.doi.org/10.5194/isprs-archives-xli-b1-475-2016.

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The process of satellite mission scheduling, which plays a significant role in rapid response to emergent disasters, e.g. earthquake, is used to allocate the observation resources and execution time to a series of imaging tasks by maximizing one or more objectives while satisfying certain given constraints. In practice, the information obtained of disaster situation changes dynamically, which accordingly leads to the dynamic imaging requirement of users. We propose a satellite scheduling model to address dynamic imaging tasks triggered by emergent disasters. The goal of proposed model is to meet the emergency response requirements so as to make an imaging plan to acquire rapid and effective information of affected area. In the model, the reward of the schedule is maximized. To solve the model, we firstly present a dynamic segmenting algorithm to partition area targets. Then the dynamic heuristic algorithm embedding in a greedy criterion is designed to obtain the optimal solution. To evaluate the model, we conduct experimental simulations in the scene of Wenchuan Earthquake. The results show that the simulated imaging plan can schedule satellites to observe a wider scope of target area. We conclude that our satellite scheduling model can optimize the usage of satellite resources so as to obtain images in disaster response in a more timely and efficient manner.

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15

Granz, A., and Y. Gao. "SS/TDMA scheduling for satellite clusters." IEEE Transactions on Communications 40, no. 3 (March 1992): 597–603. http://dx.doi.org/10.1109/26.135730.

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16

Chen, Yingguo, Ming Chen, Jun Wen, Yingwu Chen, and Wen Xiang. "An Adaptive Large Neighborhood Search Algorithm for the Satellite Data Transmission Scheduling Problem." International Journal of Aerospace Engineering 2020 (September 16, 2020): 1–12. http://dx.doi.org/10.1155/2020/5243749.

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Satellite establishes a satellite ground station to satellite link with a ground station to complete data transmission. However, in China, satellite ground stations only exist within the country. With the rapid increase in the number of satellites, effectively dispatching satellite communications and maximizing the performance of ground stations are necessary. We propose a heuristic adaptive large neighborhood search algorithm (H-ALNS) to solve the satellite data transmission scheduling (SDTS) problem. The algorithm includes two heuristic rules for generating the initial scheme and the conflict reduction process after updating the neighborhood. A heuristic task assignment method is used to select the execution time window and position for the task sequence. The adaptive operator is used to update the delete operator and insert operator weights into the H-ALNS. The quality of the generated planning scheme improved through continuous neighborhood destruction and repair. Through experimental analysis, the algorithm we propose is feasible for solving SDTS problems and surpasses the planning results acquired using other comparison algorithms. The H-ALNS has good prospects for practical engineering applications.

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17

Chen, Hao, Baorong Zhai, Jiangjiang Wu, Chun Du, and Jun Li. "A Satellite Observation Data Transmission Scheduling Algorithm Oriented to Data Topics." International Journal of Aerospace Engineering 2020 (July 1, 2020): 1–16. http://dx.doi.org/10.1155/2020/2180674.

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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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Zhang, Xiao, Yang, Liu, Chang, and Zhou. "An Effectiveness Evaluation Model for Satellite Observation and Data-Downlink Scheduling Considering Weather Uncertainties." Remote Sensing 11, no. 13 (July 8, 2019): 1621. http://dx.doi.org/10.3390/rs11131621.

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Low Earth orbit (LEO) satellites play an important role in human space activities, and market demands for commercial uses of LEO satellites have been increasing rapidly in recent years. LEO satellites mainly consist of Earth observation satellites (EOSs), the major commercial applications of which are various sorts of Earth observations, such as map making, crop growth assessment, and disaster surveillance. However, the success rates of observation tasks are influenced considerably by uncertainties in local weather conditions, inadequate sunlight, observation dip angle, and other practical factors. The available time windows (ATWs) suitable for observing given types of targets and for transmitting data back to ground receiver stations are relatively narrow. In order to utilize limited satellite resources efficiently and maximize their commercial benefits, it is necessary to evaluate the overall effectiveness of satellites and planned tasks considering various factors. In this paper, we propose a method for determining the ATWs considering the influence of sunlight angle, elevation angle, and the type of sensor equipped on the satellite. After that, we develop a satellite effectiveness evaluation (SEE) model for satellite observation and data-downlink scheduling (SODS) based on the Availability–Capacity–Profitability (ACP) framework, which is designed to evaluate the overall performance of satellites from the perspective of time resource utilization, the success rate of tasks, and profit return. The effects of weather uncertainties on the tasks’ success are considered in the SEE model, and the model can be applied to support the decision-makers on optimizing and improving task arrangements for EOSs. Finally, a case study is presented to demonstrate the effectiveness of the proposed method and verify the ACP-based SEE model. The obtained ATWs by the proposed method are compared with those by the Systems Tool Kit (STK), and the correctness of the method is thus validated.

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Li, Sheng Yi, Yi Yao Yeh, and Feng Tai Hwang. "Mission Track Coordination Based Multi-Objective Optimization for Multi-Satellite Imaging Scheduling." Applied Mechanics and Materials 284-287 (January 2013): 1494–98. http://dx.doi.org/10.4028/www.scientific.net/amm.284-287.1494.

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Satellite imaging scheduling is a complicated task been developed to ideally satisfy all requests under various constraints. A considerable amount of theoretical work has been carried out on single- or multi-satellite scheduling problems based on single-objective optimization. On the other hand, concerning multi-objective optimization in a multi-satellite scheduling scenario, few theoretical analyses have been performed. In this paper, we propose a novel imaging scheduling algorithm of multi-objective optimization for multi-satellite (MOO-MS). The concept of orbit coordination is introduced and the geometry analysis is incorporated to obtain the Pareto front as a set of trade-off solutions. Moreover, a truncated Cauchy probability distribution function (TCPDF) search algorithm is developed to efficiently obtain a sequence of tasking areas with imaging time. Simulation results show that the proposed algorithm avoids large amount of calculation and provides high quality solution within a short period of time by comparing with the single- or multi-satellite optimization scheme.

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Wang, Zhen Yong, Xiao Wei Liu, and Xue Mai Gu. "PWBA: A Novel Multicast Scheduling Algorithm for Wideband Multimedia Satellite Communications." Applied Mechanics and Materials 195-196 (August 2012): 895–900. http://dx.doi.org/10.4028/www.scientific.net/amm.195-196.895.

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Satellite multicast service expands the application of wideband multimedia satellite. Scheduling plays an important role to guarantee Quality of Service (QoS) for wideband multimedia multicast services. In this paper, considering various properties of QoS requirements of latency, throughput and priority, a PWBA multicast scheduling algorithm is proposed to balance trade-off between throughput and latency in order to providing better multimedia services in satellite networks. Comparing with the WBA and PGMF multicast scheduling policies, the proposed PWBA has better performances in both latency and throughput.

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Chen, Yuning, Ji Lu, Renjie He, and Junwei Ou. "An Efficient Local Search Heuristic for Earth Observation Satellite Integrated Scheduling." Applied Sciences 10, no. 16 (August 13, 2020): 5616. http://dx.doi.org/10.3390/app10165616.

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Earth observation satellites (EOSs) are taking a large number of pictures with increasing resolution which produce massive image data. Satellite data transmission becomes the bottleneck part in the process of EOS resource management. In this paper, we study the earth observation satellite integrated scheduling problem (EOSIS) where the imaging activities and download activities are considered integratively. We propose an integer linear programming model to formulate the problem. Due to the NP-hardness of the problem, we propose an efficient local search heuristic (ELSH) to solve problems of large size. ELSH uses a dedicated local search method to guarantee algorithm performance and efficient constraint handling mechanisms to guarantee algorithm efficiency. Numerical experimental results show that the algorithm demonstrates excellent performance on a set of benchmark instances. The ELSH achieves optimal results for all small-size instances (with 50 targets, two satellites, and three ground stations), and is very robust for large instances with up to 2000 targets. Moreover, the proposed ELSH easily dominates the state-of-the-art algorithm.

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Huang, Yixin, Zhongcheng Mu, Shufan Wu, Benjie Cui, and Yuxiao Duan. "Revising the Observation Satellite Scheduling Problem Based on Deep Reinforcement Learning." Remote Sensing 13, no. 12 (June 18, 2021): 2377. http://dx.doi.org/10.3390/rs13122377.

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Earth observation satellite task scheduling research plays a key role in space-based remote sensing services. An effective task scheduling strategy can maximize the utilization of satellite resources and obtain larger objective observation profits. In this paper, inspired by the success of deep reinforcement learning in optimization domains, the deep deterministic policy gradient algorithm is adopted to solve a time-continuous satellite task scheduling problem. Moreover, an improved graph-based minimum clique partition algorithm is proposed for preprocessing in the task clustering phase by considering the maximum task priority and the minimum observation slewing angle under constraint conditions. Experimental simulation results demonstrate that the deep reinforcement learning-based task scheduling method is feasible and performs much better than traditional metaheuristic optimization algorithms, especially in large-scale problems.

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M. Al-Saegh, Ali. "Optimal approach for building scheduling algorithm in satellite communication." International Journal of Engineering & Technology 7, no. 2.28 (May 16, 2018): 181. http://dx.doi.org/10.14419/ijet.v7i2.28.12907.

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Building scheduling algorithms in satellite communication links became a necessity according to the typical problems that satellite networks suffers from, such as congestions, jamming, mobility, atmospheric impairment, and achieving the quality of service (QoS) requirements. However, building efficient algorithms needs several considerations that should be taken into account. Such as satellite and earth station node(s), link parameters and specifications, along with the service requirements and limitations. This paper presents efficient approach for accumulating the effective considerations that the designer should employ as a framework for building proper and efficient scheduling algorithm. The proposed approach provides proper solutions to the satellite communications impairments and satisfies the quality of service requirements in satellite communication networks.

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Kennedy, Dale J., Gregory S. Parnell, and William F. Rowell. "An Expert System for Scheduling Satellite Supports." Interfaces 18, no. 6 (December 1988): 28–34. http://dx.doi.org/10.1287/inte.18.6.28.

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Karapetyan, Daniel, Snezana Mitrovic Minic, Krishna T. Malladi, and Abraham P. Punnen. "Satellite downlink scheduling problem: A case study." Omega 53 (June 2015): 115–23. http://dx.doi.org/10.1016/j.omega.2015.01.001.

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Sun, Baolin, Wenxiang Wang, Xing Xie, and Qianqing Qin. "Satellite mission scheduling based on genetic algorithm." Kybernetes 39, no. 8 (August 10, 2010): 1255–61. http://dx.doi.org/10.1108/03684921011063538.

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Tobin, G. R., and L. W. Cahill. "Maximum zeros scheduling for satellite switch TDMA." Electronics Letters 26, no. 14 (1990): 970. http://dx.doi.org/10.1049/el:19900631.

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Luo, Kaiping, Haihong Wang, Yijun Li, and Qiang Li. "High-performance technique for satellite range scheduling." Computers & Operations Research 85 (September 2017): 12–21. http://dx.doi.org/10.1016/j.cor.2017.03.012.

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Brandimarte, Paolo. "Scheduling satellite launch missions: an MILP approach." Journal of Scheduling 16, no. 1 (December 7, 2012): 29–45. http://dx.doi.org/10.1007/s10951-012-0304-y.

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Vazquez, Antonio J., and R. Scott Erwin. "On the tractability of satellite range scheduling." Optimization Letters 9, no. 2 (April 10, 2014): 311–27. http://dx.doi.org/10.1007/s11590-014-0744-8.

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Anastasiou, E., Z. Tsiropoulos, S. Fountas, A. Osann, D. Protic, M. Simeonidou, and L. Xenidis. "User requirements for a satellite-based advisory platform." Advances in Animal Biosciences 8, no. 2 (June 1, 2017): 368–71. http://dx.doi.org/10.1017/s2040470017000942.

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APOLLO, a newly funded H2020 EU project will develop an agricultural advisory platform for small farmers based on Copernicus Sentinel satellites. It will provide services for tillage scheduling, irrigation scheduling, crop growth monitoring and yield estimation. The aim of this study was to identify the farmers’ requirements of the APOLLO platform. In total 121 farmers were interviewed in Spain, Serbia and Greece. More than 90% of the farmers pointed out that smart agriculture and use of satellite data in agriculture are important. Additionally, more than 80% want to have access to historical data and a flexible subscription policy to the platform according to their needs and use. However, significant differences exist among farmers of these countries in terms of technology awareness and penetration, which should be taken into consideration for developing a successful platform.

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Audah, Lukman, Zhili Sun, and Haitham Cruickshank. "QoS based Admission Control using Multipath Scheduler for IP over Satellite Networks." International Journal of Electrical and Computer Engineering (IJECE) 7, no. 6 (December 1, 2017): 2958. http://dx.doi.org/10.11591/ijece.v7i6.pp2958-2969.

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<p>This paper presents a novel scheduling algorithm to support quality of service (QoS) for multiservice applications over integrated satellite and terrestrial networks using admission control system with multipath selection capabilities. The algorithm exploits the multipath routing paradigm over LEO and GEO satellites constellation in order to achieve optimum end-to-end QoS of the client-server Internet architecture for HTTP web service, file transfer, video streaming and VoIP applications. The proposed multipath scheduler over the satellite networks advocates load balancing technique based on optimum time-bandwidth in order to accommodate the burst of application traffics. The method tries to balance the bandwidth load and queue length on each link over satellite in order to fulfil the optimum QoS level for each traffic type. Each connection of a traffic type will be routed over a link with the least bandwidth load and queue length at current time in order to avoid congestion state. The multipath routing scheduling decision is based on per connection granularity so that packet reordering at the receiver side could be avoided. The performance evaluation of IP over satellites has been carried out using multiple connections, different file sizes and bit-error-rate (BER) variations to measure the packet delay, loss ratio and throughput.</p>

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Chen, Peiguang, Zihao Tian, Dong Wang, and Yeyang Zhu. "Research on Power Data and Transmission Service Based on Satellite Resource Scheduling Algorithm." E3S Web of Conferences 292 (2021): 01024. http://dx.doi.org/10.1051/e3sconf/202129201024.

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Significant improvement has been made in communication capability with the development of satellite communication technology, which plays a vital role in the application of power coefficient collection and transmission. The technological development of power Internet of Things contributes to the satellite resource optimization scheduling algorithm so that the requirements for satellite data of different subscribers and different priorities can be met to the maximum extent in a short period of time. Given this background, this paper proposed an optimized satellite resource scheduling algorithm that integrated family eugenics with simulated annealing.

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Zhai, Xuejun, Xiaonan Niu, Hong Tang, Lixin Wu, and Yonglin Shen. "Robust Satellite Scheduling Approach for Dynamic Emergency Tasks." Mathematical Problems in Engineering 2015 (2015): 1–20. http://dx.doi.org/10.1155/2015/482923.

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Earth observation satellites play a significant role in rapid responses to emergent events on the Earth’s surface, for example, earthquakes. In this paper, we propose a robust satellite scheduling model to address a sequence of emergency tasks, in which both the profit and robustness of the schedule are simultaneously maximized in each stage. Both the multiobjective genetic algorithm NSGA2 and rule-based heuristic algorithm are employed to obtain solutions of the model. NSGA2 is used to obtain a flexible and highly robust initial schedule. When every set of emergency tasks arrives, a combined algorithm called HA-NSGA2 is used to adjust the initial schedule. The heuristic algorithm (HA) is designed to insert these tasks dynamically to the waiting queue of the initial schedule. Then the multiobjective genetic algorithm NSGA2 is employed to find the optimal solution that has maximum revenue and robustness. Meanwhile, to improve the revenue and resource utilization, we adopt a compact task merging strategy considering the duration of task execution in the heuristic algorithm. Several experiments are used to evaluate the performance of HA-NSGA2. All simulation experiments show that the performance of HA-NSGA2 is significantly improved.

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Gao, Peng, Yue Jin Tan, Ju Fang Li, and Ren Jie He. "An Ant Colony Algorithm for Remote Satellite and Ground Integration Scheduling Problem in Parallel Environment." Advanced Materials Research 791-793 (September 2013): 1341–46. http://dx.doi.org/10.4028/www.scientific.net/amr.791-793.1341.

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The algorithms for solving the remote satellite scheduling problem are less effective usually in single computing environment. This paper designed a framework of ant colony algorithm for remote satellite and ground integration scheduling problem in the parallel environment, and given the detail of key steps in the algorithm. Experiments are show at the end of this paper to prove effective and validation.

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Ling, Xiao Dong, Wei Kang Zhu, Jin Mei Wu, and Xiao Yue Wu. "Research of Multi-Satellite TT&C Scheduling Problem." Applied Mechanics and Materials 263-266 (December 2012): 476–84. http://dx.doi.org/10.4028/www.scientific.net/amm.263-266.476.

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Multi-Satellite TT&C Scheduling Problem（MuSTSP） is to the keypoint of help doing high level design for space TT&C network and the conflict is the most important thing which result in MuSTSP. In this paper, the conflict is aboratively analyzed. Some new conceptions are proposed. Then a new heuristic scheduling method based on conflict-resolvation is introduced. A simple example is given to elaborate the feasibility of this method.

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Jang, Seongik, and Hoeseok Yang. "A Real-Time Scheduling Approach to Mitigation of Li-Ion Battery Aging in Low Earth Orbit Satellite Systems." Electronics 10, no. 1 (January 4, 2021): 86. http://dx.doi.org/10.3390/electronics10010086.

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Thanks to their higher performance compared to conventional batteries, lithium-ion (Li-ion) batteries have recently become popular as a power source in many electronic systems. However, Li-ion batteries are known to suffer from an aging issue: the available capacity is gradually degraded as the operation goes by. The impact of aging is particularly critical to satellite systems where no maintenance is available after the initial deployment. Recently, a real-time scheduling framework was proposed to decelerate the aging of Li-ion batteries. However, this framework simply relies on the fact that the elevated temperature results in a worse lifespan of the battery. In contrast to this, in this paper, we argue that the reduced temperature may actually cause an adverse effect in the battery lifetime when considering satellite environments. To evidently demonstrate this anomaly, we extend an open-source Li-ion battery aging simulator to consider the temperature-dependent aging characteristics of the Li-ion batteries. Then, a couple of alternative scheduling policies that better suit the target satellite systems are evaluated in the simulator in comparison with the existing scheduling policies. Our simulation results show that the existing scheduling method, which does not consider the satellite temperature environments, rather deteriorates the lifespan of battery and the proposed scheduling technique can extend the lifespan by up to 65.51%.

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Leng, Tao, Xiaoyao Li, Dongwei Hu, Gaofeng Cui, and Weidong Wang. "Collaborative Computing and Resource Allocation for LEO Satellite-Assisted Internet of Things." Wireless Communications and Mobile Computing 2021 (September 15, 2021): 1–12. http://dx.doi.org/10.1155/2021/4212548.

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Satellite-assisted internet of things (S-IoT), especially the S-IoT based on low earth orbit (LEO) satellite, plays an important role in future wireless systems. However, the limited on-board communication and computing resource and high mobility of LEO satellites make it hard to provide satisfied service for IoT users. To maximize the task completion rate under latency constraints, collaborative computing and resource allocation among LEO networks are jointly investigated in this paper, and the joint task offloading, scheduling, and resource allocation is formulated as a dynamic mixed-integer problem. To tack the complex problem, we decouple it into two subproblems with low complexity. First, the max-min fairness is adopted to minimize the maximum latency via optimal resource allocation with fixed task assignment. Then, the joint task offloading and scheduling is formulated as a Markov decision process with optimal communication and computing resource allocation, and deep reinforcement learning is utilized to obtain long-term benefits. Simulation results show that the proposed scheme has superior performance compared with other referred schemes.

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Pemberton, Joseph C. "Solving Over-Constrained Satellite Remote-Sensing Scheduling Problems." Electronic Notes in Discrete Mathematics 4 (January 2000): 54. http://dx.doi.org/10.1016/s1571-0653(05)80105-2.

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Lee, Sang-Un. "Polynomial Time Algorithm for Satellite Communications Scheduling Problem." Journal of Korean Institute of Information Technology 13, no. 4 (April 30, 2015): 27. http://dx.doi.org/10.14801/jkiit.2015.13.4.27.

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Liao, Da-Yin, and Yu-Tsung Yang. "Imaging Order Scheduling of an Earth Observation Satellite." IEEE Transactions on Systems, Man and Cybernetics, Part C (Applications and Reviews) 37, no. 5 (September 2007): 794–802. http://dx.doi.org/10.1109/tsmcc.2007.900668.

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Lin, W. C., D. Y. Liao, C. Y. Liu, and Y. Y. Lee. "Daily Imaging Scheduling of an Earth Observation Satellite." IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans 35, no. 2 (March 2005): 213–23. http://dx.doi.org/10.1109/tsmca.2005.843380.

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Gooley, T. D., J. J. Borsi, and J. T. Moore. "Automating Air Force Satellite control Network (AFSCN) scheduling." Mathematical and Computer Modelling 24, no. 2 (July 1996): 91–101. http://dx.doi.org/10.1016/0895-7177(96)00093-3.

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Baek, Seung-Woo, Kyeum-Rae Cho, Dae-Woo Lee, and Hae-Dong Kim. "A Comparison of Scheduling Optimization Algorithm for the Efficient Satellite Mission Scheduling Operation." Journal of the Korean Society for Aeronautical & Space Sciences 38, no. 1 (January 1, 2010): 48–57. http://dx.doi.org/10.5139/jksas.2010.38.1.048.

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He, Lei, Xiao-Lu Liu, Ying-Wu Chen, Li-Ning Xing, and Ke Liu. "Hierarchical scheduling for real-time agile satellite task scheduling in a dynamic environment." Advances in Space Research 63, no. 2 (January 2019): 897–912. http://dx.doi.org/10.1016/j.asr.2018.10.007.

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Gao, Ke Bin, Guo Hua Wu, and Jiang Han Zhu. "Multi-Satellite Observation Scheduling Based on a Hybrid Ant Colony Optimization." Advanced Materials Research 765-767 (September 2013): 532–36. http://dx.doi.org/10.4028/www.scientific.net/amr.765-767.532.

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in this paper, we attempted to find an effective method to resolve multi-satellite observation scheduling problems. Firstly, an acyclic directed graph model for multi-satellite observation scheduling was constructed. Secondly, based on the graph model, we presented a novel hybrid ant colony optimization mixed with the iteration local search algorithm (ACO-ILS) to produce high quality schedules. At last, extensive experimental simulations demonstrated that the proposed ACO-ILS algorithm is very efficient.

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Song, Bingyu, Feng Yao, Yuning Chen, Yingguo Chen, and Yingwu Chen. "A Hybrid Genetic Algorithm for Satellite Image Downlink Scheduling Problem." Discrete Dynamics in Nature and Society 2018 (2018): 1–11. http://dx.doi.org/10.1155/2018/1531452.

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The satellite image downlink scheduling problem (SIDSP) is included in satellite mission planning as an important part. A customer demand is finished only if the corresponding images are eventually downloaded. Due to the growing customer demands and the limited ground resources, SIDSP is an oversubscribed scheduling problem. In this paper, we investigate SIDSP with the case study of China’s commercial remote sensing satellite constellation (SuperView-1) and exploit the serial scheduling scheme for solving it. The idea is first determining a permutation of the downlink requests and then producing a schedule from the given ordered requests. A schedule generation algorithm (SGA) is proposed to assign the downlink time window for each scheduled request according to a given request permutation. A hybrid genetic algorithm (HGA) combined with neighborhood search is proposed to optimize the downlink request permutation with the purpose of maximizing the utility function. Experimental results on six groups of instances with different density demonstrate the effectiveness of the proposed approach.

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Zhang, Ye, Xiaoxuan Hu, Waiming Zhu, and Peng Jin. "Solving the Observing and Downloading Integrated Scheduling Problem of Earth Observation Satellite with a Quantum Genetic Algorithm." Journal of Systems Science and Information 6, no. 5 (November 5, 2018): 399–420. http://dx.doi.org/10.21078/jssi-2018-399-22.

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Abstract This paper addresses the integrated Earth observation satellite scheduling problem. It is a complicated problem because observing and downloading operations are both involved. We use an acyclic directed graph model to describe the observing and downloading integrated scheduling problem. Based on the model which considering energy constraints and storage capacity constraints, we develop an efficient solving method using a novel quantum genetic algorithm. We design a new encoding and decoding scheme that can generate feasible solution and increase the diversity of the population. The results of the simulation experiments show that the proposed method solves the integrated Earth observation satellite scheduling problem with good performance and outperforms the genetic algorithm and greedy algorithm on all instances.

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Li, Cheng, Fu Jun Luo, and Wen Yi Zhang. "A Study on Satellite-Ground Link of the Satellite Receiving Station." Advanced Materials Research 487 (March 2012): 143–47. http://dx.doi.org/10.4028/www.scientific.net/amr.487.143.

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The analysis of the linkage between ground station and satellite is the premise of scheduling the ground data receiving task, which includes the time window calculation, satellite relative antenna's azimuth, elevation angle calculation. This article studies the linkage between ground station and satellite. Meanwhile, with the aid of the world wind platform, it develops the demo software of the 3-dimensional modeling to study the simulation to link the star, and it can calculate time window, the azimuth angle between the land and elevation angle. It proves that software-testing results agree with STK software calculation results. Thus, the software is reliable to provide the scientific basis for the selection of ground stations' location and nets planning.

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Narayanan, Shreeram, Soham Jagtap, Arnold Johnson Fonseca, and Reena Sonkusare. "Cloud Cover Avoidance in Satellite Systems." International Journal of Online and Biomedical Engineering (iJOE) 16, no. 13 (November 17, 2020): 112. http://dx.doi.org/10.3991/ijoe.v16i13.18559.

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<span id="docs-internal-guid-41420025-7fff-e714-8d51-73d40b2b7340"><span>Cloud cover is primarily a major difficulty in the acquisition of optical satellite images and has a negative impact on the efficiency of data scheduling. Along with data scheduling, the computational power required is also increasing. Recent advances in an extensive variety of technologies have resulted in an explosion in the amount of data. Different methodologies have been used for Object detection in remote sensing images but it remains a challenge because of its diversity and complex backgrounds. In this paper, a cloud cover detection technique based on Convolutional Neural Networks is proposed for remote sensing images. The classifying model uses a neural network where the underlying features are used to classify the image as useful or not. Results illustrate that the proposed method outperforms other state of the art methods that exist. Once classified, it will be transmitted from the satellite to the earth giving the researchers only convenient pictures to study. This will help to save a massive amount of computation, expense and time.</span></span>

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