基于计算空时图的星地一体网车辆互联网救援空间地面协同SFC流调度策略

IF 3.7 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Yingjie Deng, Yu Liu, Yumei Wang, Konglin Zhu, Peng Wu, Lu Cao, Wen Sun, Jingwen Xu
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引用次数: 0

摘要

卫星星座的广泛覆盖使得星地一体化网络(STIN)在地面网络有限的偏远或灾区的车联网(IoVs)救援中成为通信和计算服务的关键解决方案。为了优化网络资源利用率和服务质量,将业务功能链(SFC)集成到支持stin的车联网救援系统中变得至关重要。然而,传统的基于sfc的STIN系统在流调度灵活性方面面临挑战,这源于子任务在配备虚拟网络功能(VNFs)的卫星上的顺序执行。这导致在数据量减少和轨道上产生的额外通信和计算能量成本之间进行权衡。为了解决这一问题,本文引入了空间地面协同SFC (SGC-SFC)流调度策略。该策略可以根据网络条件,在配备vnf的卫星或地面车辆编队上执行子任务。首先,针对具有SFC的基于stin的车联网救援系统,建立了计算-时空图(CSTG)模型,该模型将计算层集成到时空图(STG)中,准确捕捉了stin的车联网救援系统中SFC的数据体积缩减特征和顺序执行约束。其次,设计了一种SGC-SFC流调度算法,以确定一组能量消耗最小、可处理数据量最大的可行路径。仿真结果验证了所提出的SGC-SFC在不同条件下的有效性和鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Space Ground Collaborative SFC Flow Scheduling Strategy in Satellite–Terrestrial Integrated Network–Enabled Internet of Vehicles Rescuing Based on Computation–Space–Time Graph

Space Ground Collaborative SFC Flow Scheduling Strategy in Satellite–Terrestrial Integrated Network–Enabled Internet of Vehicles Rescuing Based on Computation–Space–Time Graph

The extensive coverage of satellite constellations has rendered the satellite–terrestrial integrated network (STIN) a pivotal solution for communication and computation services in internet of vehicles (IoVs) rescuing in remote or disaster areas with limited terrestrial networks. To optimise network resource utilisation and service quality, the integration of the service function chain (SFC) into STIN-enabled IoV rescuing systems has become essential. However, traditional SFC-based STIN systems encounter challenges in flow scheduling flexibility, stemming from the sequential execution of subtasks on satellites equipped with virtual network functions (VNFs). This leads to a trade-off between data volume reduction and the additional communication and computation energy costs incurred in the orbit. To address this issue, this paper introduces a space ground collaborative SFC (SGC-SFC) flow scheduling strategy. This strategy enables the execution of subtasks on either VNF-equipped satellites or the ground vehicle formation, contingent on network conditions. Firstly, we carry out a computation–space–time graph (CSTG) model specifically for the STIN-enabled IoV rescuing system with SFC. This model integrates the computational layer into the space–time graph (STG), accurately capturing the data volume reduction characteristics and sequential execution constraints of SFC in the STIN-enabled IoV rescuing system. Secondly, a SGC-SFC flow scheduling algorithm is designed to identify a set of feasible paths with minimal energy cost and maximum processable data volume. Simulation results validate the effectiveness and robustness of our proposed SGC-SFC under diverse conditions.

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来源期刊
International Journal of Intelligent Systems
International Journal of Intelligent Systems 工程技术-计算机:人工智能
CiteScore
11.30
自引率
14.30%
发文量
304
审稿时长
9 months
期刊介绍: The International Journal of Intelligent Systems serves as a forum for individuals interested in tapping into the vast theories based on intelligent systems construction. With its peer-reviewed format, the journal explores several fascinating editorials written by today''s experts in the field. Because new developments are being introduced each day, there''s much to be learned — examination, analysis creation, information retrieval, man–computer interactions, and more. The International Journal of Intelligent Systems uses charts and illustrations to demonstrate these ground-breaking issues, and encourages readers to share their thoughts and experiences.
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