Beam scheduling is one of the most important issues regarding data relay satellite systems,which can improve the utilization efficiency of limited system resources by programming beam allocation for relay missions.The...Beam scheduling is one of the most important issues regarding data relay satellite systems,which can improve the utilization efficiency of limited system resources by programming beam allocation for relay missions.The ever-increasing relay missions create a substantial challenge for beam scheduling due to an increase in different mission demands.The cooperative usage of different beams further increases the complexity of this problem.Therefore,we develop a novel optimization method to solve the beam scheduling problem for the scenario of various mission demands in the data relay satellite system(DRSS).Based on the analysis of mission demands and resource features,we first construct a heterogeneous parallel machines scheduling model to formulate the beam scheduling problem in the DRSS.To solve this complicated model,we investigate the matching method between mission demands and beam resources,and introduce two concepts,the loose duration and the number of available beams,to make the matching process more effective.Then,the following three algorithms are proposed.Our first approach,the maximized completion probability algorithm(MCPA),applies a greedy strategy based on the new concepts to allocate beams for missions;and two improved versions of this algorithm are also presented,which employ the strategies of mission insertion optimization and mission sequence optimization,respectively.Our simulation results show that the proposed algorithms are superior to the existing algorithms in terms of the scheduled missions,the weight of scheduled missions,and the processing time,which significantly improves the performance of beam scheduling in the DRSS.展开更多
基金This work was supported in part by the National Key Research and Development Program of China under Grant 2020YFB1804800in part by the National Natural Science Foundation of China under Grant 61922050.
文摘Beam scheduling is one of the most important issues regarding data relay satellite systems,which can improve the utilization efficiency of limited system resources by programming beam allocation for relay missions.The ever-increasing relay missions create a substantial challenge for beam scheduling due to an increase in different mission demands.The cooperative usage of different beams further increases the complexity of this problem.Therefore,we develop a novel optimization method to solve the beam scheduling problem for the scenario of various mission demands in the data relay satellite system(DRSS).Based on the analysis of mission demands and resource features,we first construct a heterogeneous parallel machines scheduling model to formulate the beam scheduling problem in the DRSS.To solve this complicated model,we investigate the matching method between mission demands and beam resources,and introduce two concepts,the loose duration and the number of available beams,to make the matching process more effective.Then,the following three algorithms are proposed.Our first approach,the maximized completion probability algorithm(MCPA),applies a greedy strategy based on the new concepts to allocate beams for missions;and two improved versions of this algorithm are also presented,which employ the strategies of mission insertion optimization and mission sequence optimization,respectively.Our simulation results show that the proposed algorithms are superior to the existing algorithms in terms of the scheduled missions,the weight of scheduled missions,and the processing time,which significantly improves the performance of beam scheduling in the DRSS.
