基于时变资源图的天地一体化网络资源模型

Long Chen, Feilong Tang, Zhetao Li, L. Yang, Jiadi Yu, Bin Yao
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引用次数: 9

摘要

空间-地面综合网络资源的有效建模是空间-地面综合网络资源建模的关键和难点。现有的工作并不适用于STINs,因为它们缺乏对不同运动模式和波动荷载的共同考虑。本文从资源的角度出发,提出了时变资源图(TVRG)来对stis进行建模。首先,我们提出了STIN迁移模型来统一建模STIN中不同的运动模式。然后,我们提出了一种分层资源建模和抽象(RMA)方法,通过将可预测的拓扑和波动负载的影响编码为状态,将节点资源的演化建模为马尔可夫过程。此外,我们提出了一种低复杂度的领域资源抽象算法,该算法在资源能力上定义了两个基于移动性和负载感知的偏序。最后,我们提出了一种高效的基于tvrg的资源调度(TRS)算法,用于时间敏感和带宽密集型数据流,具有多级按需调度能力。综合仿真结果表明,RMA-TRS在吞吐量、端到端延迟和流完成时间方面优于相关方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Time-Varying Resource Graph Based Resource Model for Space-Terrestrial Integrated Networks
It is critical but difficult to efficiently model re-sources in space-terrestrial integrated networks (STINs). Existing work is not applicable to STINs because they lack the joint consideration of different movement patterns and fluctuating loads. In this paper, we propose the time-varying resource graph (TVRG) to model STINs from the resource perspective. Firstly, we propose the STIN mobility model to uniformly model different movement patterns in STINs. Then, we propose a layered Resource Modeling and Abstraction (RMA) approach, where evolutions of node resources are modeled as Markov processes, by encoding predictable topologies and influences of fluctuating loads as states. Besides, we propose the low-complexity domain resource abstraction algorithm by defining two mobility-based and load-aware partial orders on resource abilities. Finally, we propose an efficient TVRG-based Resource Scheduling (TRS) algorithm for time-sensitive and bandwidth-intensive data flows, with the multi-level on-demand scheduling ability. Comprehensive simulation results demonstrate that the RMA-TRS outperforms related schemes in terms of throughput, end-to-end delay and flow completion time.
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