Resources Scheduling Algorithm for Multi-relay-Satellite System with Multi-restriction

Zhao, Weihu; Xue, Yali; Xia, Guijin; Ren, Shuai; Zhang, Mingjiang

doi:10.1109/icitbs.2019.00117

Cited by 2 publications

(1 citation statement)

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“…Scholars from different countries have proposed resource scheduling algorithms with different emphasis on different research backgrounds, resource characteristics and task requirements. In reference [4], A scheduling algorithm based on ant genetic algorithm is proposed, but the multi-dimensionality of resources is not considered. In reference [5] and [6], a feature-based TT&C resource scheduling algorithm is established for the satellite visible window with satellite task decomposition rather than independent fragmentation.…”

Section: Introductionmentioning

confidence: 99%

Resource cooperative scheduling algorithm for SAGIN

Luo²,

Zhao³

et al. 2022

2nd International Conference on Signal Image Processing and Communication (ICSIPC 2022)

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Resource scheduling technology as an important means to achieve the optimal allocation of SAGIN resources, plays a vital role in Earth observation, emergency communications and other fields, through the in-depth understanding and analysis of the research status of the integrated network resource scheduling field, the current resource scheduling technology is not yet perfect, it is difficult to meet the multi-satellite collaboration, network topology real-time changes, massive users as the characteristics of the scheduling needs. Starting from the research point of multi-dimensional resources, this paper considers the synergy between resources, proposes a multi-dimensional resource vector model, and on this basis proposes a multi-dimensional resource collaborative optimization scheduling algorithm to achieve unified scheduling from the global perspective. In the simulation experiment, it is proved that the indicators such as the number of task completions, total tasks revenues, average revenue and scheduling decision-making time can be effectively improved, among which the number of task completions is increased by 10%-30%, the total tasks revenue is increased by 30%-60%, and the scheduling decision-making time is saved by about 30%.

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Section: Introductionmentioning

confidence: 99%