卫星调度问题的Web接口

F. Xhafa, C. García, Admir Barolli, M. Takizawa
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引用次数: 2

摘要

任务规划在卫星控制系统中起着重要的作用,特别是随着卫星数量的增加和任务规划的复杂化。在一般情况下,卫星任务调度包括将观测、通信等任务分配给资源(航天器、卫星、地面站)。例如,在地面站调度中,其目标是计算出卫星与地面站操作团队之间通信的最优规划。由于sc和GSs之间的通信可以在特定的窗口时间内完成,因此该问题也可以视为窗口时间调度问题。所需的通信时间通常远远小于SCs对gps的可见窗口,但会产生冲突,使问题受到高度约束。在这项工作中,我们提出了一个通过各种启发式方法解决卫星调度问题的Web界面。Web界面使用户能够通过选择启发式方法,如局部搜索方法(爬山、模拟退火和禁忌搜索)和基于种群的方法(遗传算法和变体),远程解决他们的问题实例。用户可以选择通过STK模拟工具包解决以前生成的实例,或者生成自己的问题实例。启发式方法很容易配置,因此用户可以模拟各种场景、问题大小等。启发式方法的执行是在HPC集群基础设施上完成的,该基础设施支持各种求解器的有效执行。此外,Web应用程序允许用户跟踪其执行情况,并与其他用户共享问题实例。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Web Interface for Satellite Scheduling Problems
Mission planning plays an important role in satellite control systems, especially with increase of number of satellites and more complex missions to be planned. In a general setting, the satellite mission scheduling consists in allocating tasks such as observation, communication, etc. to resources (spacecrafts (SCs), satellites, ground stations). For instance, in ground station scheduling the aim is to compute an optimal planning of communications between satellites and operations teams of Ground Station (GS). Because the communication between SCs and GSs can be done during specific window times, this problem can also be seen as a window time scheduling problem. The required communication time is usually quite smaller than the window of visibility of SCs to GSs, however, clashes are produced, making the problem highly constrained. In this work we present a Web interface for solving satellite scheduling problems through various heuristic methods. The Web interface enables the users to remotely solve their problem instances through a selection of heuristic methods such as local search methods (Hill Climbing, Simulated Annealing and Tabu Search) and population-based methods (Genetic Algorithms and variants). The user can select to solve previously generated instances by the STK simulation toolkit or generate their own problem instances. The heuristic methods are easily configurable so that users can simulate a variety of scenarios, problem sizes, etc. The execution of the heuristics methods is done at a HPC Cluster infrastructure supporting efficient execution of various solvers. Additionally, the Web application allows users to keep track of their executions as well as to share problem instances with other users.
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