Research and Simulation of Space-based Resource Scheduling Based on Improved Ant Colony Algorithm

doi:10.12068/j.issn.1005-3026.2023.02.003

Abstract

Abstract: The satellite resources of the space-based information network are limited.It is difficult to upgrade in orbit and the delay of inter-link communication is high， which results in inefficient processing of large-scale concurrent tasks. A dynamic priority-based task model is constructed for situations where the task is simple and concurrent and each task is handled by one node. A resource model based on fuzzy clustering theory is constructed for computing and storage resources in space-based information network. Space-based resource scheduling strategy based on improved ant colony algorithm is proposed. Load balancing factor is introduced. Pheromone update rule is changed. Task allocation strategy is adjusted. Min-Min-algorithm is combined to promote task execution and resource allocation. Simulation results show that compared with the comparison algorithm， the task completion time is 29.2% shorter， the task cumulative value is 37.9% higher， the resource load equilibrium degree is 75.5% smaller， and the resource utilization rate is 22.4% higher， which verifies the excellence of the algorithm.

Key words: space-based information network; task dynamic sorting; resource clustering; ant colony algorithm; resource scheduling

CLC Number:

TP20

GENG Rong， ZHANG Zhao， NIU Tian-shui， WANG Yu-fei. Research and Simulation of Space-based Resource Scheduling Based on Improved Ant Colony Algorithm[J]. Journal of Northeastern University(Natural Science), 2023, 44(2): 168-176.

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