Routing optimization of small satellite networks based on multi-commodity flow

Xiaolin Xu, Yu Zhang*, Jihua Lu

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationMachine Learning and Intelligent Communications - Second International Conference, MLICOM 2017, Proceedings
EditorsXuemai Gu, Gongliang Liu, Bo Li
PublisherSpringer Verlag
Pages355-363
Number of pages9
ISBN (Print)9783319735634
DOIs
Publication statusPublished - 2018
Event2nd International Conference on Machine Learning and Intelligent Communications, MLICOM 2017 - Weihai, China
Duration: 5 Aug 20176 Aug 2017

Publication series

NameLecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
Volume226 LNICST
ISSN (Print)1867-8211

Conference

Conference2nd International Conference on Machine Learning and Intelligent Communications, MLICOM 2017
Country/TerritoryChina
CityWeihai
Period5/08/176/08/17

Keywords

  • Approximation algorithm
  • Concurrent flow
  • Multi-commodity flow
  • Routing optimization
  • Satellite network

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