Machine Learning and Intelligent Communications. Second International Conference, MLICOM 2017, Weihai, China, August 5-6, 2017, Proceedings, Part I

Research Article

Routing Optimization of Small Satellite Networks Based on Multi-commodity Flow

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  • @INPROCEEDINGS{10.1007/978-3-319-73564-1_35,
        author={Xiaolin Xu and Yu Zhang and Jihua Lu},
        title={Routing Optimization of Small Satellite Networks Based on Multi-commodity Flow},
        proceedings={Machine Learning and Intelligent Communications. Second International Conference, MLICOM 2017, Weihai, China, August 5-6, 2017, Proceedings, Part I},
        proceedings_a={MLICOM},
        year={2018},
        month={2},
        keywords={Satellite network Multi-commodity flow Routing optimization Approximation algorithm Concurrent flow},
        doi={10.1007/978-3-319-73564-1_35}
    }
    
  • Xiaolin Xu
    Yu Zhang
    Jihua Lu
    Year: 2018
    Routing Optimization of Small Satellite Networks Based on Multi-commodity Flow
    MLICOM
    Springer
    DOI: 10.1007/978-3-319-73564-1_35
Xiaolin Xu1,*, Yu Zhang,*, Jihua Lu1,*
  • 1: Beijing Institute of Technology
*Contact email: 2120150826@bit.edu.cn, yuzhang@bit.edu.cn, lujihua@bit.edu.cn

Abstract

As the scale of small satellite network is not large and the transmission cost is high, it is necessary to optimize the routing problem. We apply the traditional time-expanded graph to model the data acquisition of small satellite network so that we can formulate the data acquisition into a multi-commodity concurrent flow optimization problem (MCFP) aiming at maximizing the throughput. We use an approximation method to accelerate the solution for MCFP and make global optimization of routing between satellite network nodes. After the quantitative comparison between our MCFP algorithm and general augmented path maximum flow algorithm and exploring the detail of the algorithm, we verify the approximation algorithm’s reasonable selection of routing optimization in small satellite network node communication.