An Ensemble of Heuristic Adaptive Contract Net Protocol for Efficient Dynamic Data Relay Satellite Scheduling Problem

Task scheduling in data relay satellite networks (DRSNs) is subject to dynamic disruptions such as resource failures, sudden surges in task demands, and variations in service duration requirements. These disturbances may degrade the performance of pre-established scheduling plans. To improve adaptab...

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Bibliographic Details
Published in:Aerospace Vol. 12; no. 8; p. 749
Main Authors: Liu, Manyi, Wu, Guohua, Gu, Yi, Luo, Qizhang
Format: Journal Article
Language:English
Published: Basel MDPI AG 01.08.2025
Subjects:
adaptive
Algorithms
Communication
contract net protocol
Data transmission
dynamic data relay satellite scheduling
Ground stations
Heuristic
Integer programming
Planning
Power supply
Relay satellites
Remote sensing
Robustness
Satellite networks
Satellites
Scheduling
Sensitivity analysis
Surges
Systems stability
Task scheduling
ISSN:2226-4310, 2226-4310
Online Access:Get full text
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Summary:Task scheduling in data relay satellite networks (DRSNs) is subject to dynamic disruptions such as resource failures, sudden surges in task demands, and variations in service duration requirements. These disturbances may degrade the performance of pre-established scheduling plans. To improve adaptability and robustness under such uncertainties, this paper presents a dynamic scheduling model for DRSN that integrates comprehensive task constraints and link connectivity requirements. The model aims to maximize overall task utility while minimizing deviations from the original schedule. To efficiently solve this problem, an ensemble heuristic adaptive contract net protocol (EH-ACNP) is developed, which supports dynamic scheduling strategy adaptation and efficient rescheduling through iterative negotiations. Extensive simulation results show that, in scenarios with sudden task surges, the proposed method achieves a 3.1% improvement in yield compared to the state-of-the-art dynamic scheduling algorithm HMCNP, and it also outperforms HMCNP in scenarios involving resource interruptions. Sensitivity analysis further indicates that the algorithm maintains strong robustness when the disposal rate parameter exceeds 0.2. These results highlight the practical potential of the EH-ACNP for dynamic scheduling in complex and uncertain DRSN environments.
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ISSN:2226-4310
2226-4310
DOI:10.3390/aerospace12080749