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Enhanced time-expanded graph for space information network modeling
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AI
DOI：10.1007/s11432-020-3202-2.png)
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Space information networks (SINs) are responsible for communications, information processing, and earth observation. Traditional time-expanded graphs (TEG) cannot represent the observation, energy, and transceiver resources. Therefore, we propose the enhanced time-expanded graph (ETEG) to jointly model the resource elements of SINs. First, we utilize snapshot graphs to characterize the time-varying properties of the resources. Next, we introduce virtual links and nodes to enhance the TEG, which transforms the transceiver and observation resource constraints into normal capacity and flow conservation ones and simplifies the energy constraints. Then, the maximum flow algorithm is modified to optimally schedule the data flow in SIN. With the ETEG-based maximum flow algorithm, the resources can be jointly optimally scheduled. Finally, the simulation results demonstrate the efficiency and effectiveness of our ETEG.
Keyword:
enhanced time-expanded graph
space information network
network modeling
heterogeneous resource modeling
joint scheduling
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7.6
论文数:
4.9K
被引数:
8.9K
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