IDEAS home Printed from https://ideas.repec.org/a/pal/jorsoc/v54y2003i4d10.1057_palgrave.jors.2601489.html
   My bibliography  Save this article

Optimal routing in non-geostationary satellite ATM networks with intersatellite link capacity constraints

Author

Listed:
  • H Lee

    (Mobile Telecommunication Research Laboratory, ETRI)

  • D H Ahn

    (Radio and Broadcasting Technology Laboratory, ETRI)

  • S Kim

    (Korea Advanced Institute of Science and Technology)

Abstract

The trend toward broadband communications in space is foreseeable, and its features predestine ATM as the basic mode of operation. Some of the low and medium earth orbit satellite concepts make use of intersatellite links (ISLs) to provide global connectivity with minimal usage of terrestrial fixed network resources. Interconnecting neighbouring satellites with ISLs results in a partially meshed switching subnetwork in space. The ISLs have a time-varying distance or may even lose sight of each other. This feature of the ISL topology dynamics significantly increases the complexity of connection-oriented network operation and routing. We deal with the routing problem to minimize the virtual path connection handover rate and path delay in the time-varying ISL subnetwork topology with ISL capacity constraints. A heuristic algorithm is proposed to deal with this problem, which is based on Lagrangean relaxation and dynamic programming. When there is sufficient capacity at every ISL, the algorithm produces an optimal solution easily using only dynamic programming. For evaluation of our algorithm, some computational results have been presented. These results show that our optimization algorithm can produce a solution close to an optimal solution when there exist ISL capacity constraints.

Suggested Citation

  • H Lee & D H Ahn & S Kim, 2003. "Optimal routing in non-geostationary satellite ATM networks with intersatellite link capacity constraints," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(4), pages 401-409, April.
  • Handle: RePEc:pal:jorsoc:v:54:y:2003:i:4:d:10.1057_palgrave.jors.2601489
    DOI: 10.1057/palgrave.jors.2601489
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/palgrave.jors.2601489
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1057/palgrave.jors.2601489?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Marshall L. Fisher, 1981. "The Lagrangian Relaxation Method for Solving Integer Programming Problems," Management Science, INFORMS, vol. 27(1), pages 1-18, January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wolosewicz, Cathy & Dauzère-Pérès, Stéphane & Aggoune, Riad, 2015. "A Lagrangian heuristic for an integrated lot-sizing and fixed scheduling problem," European Journal of Operational Research, Elsevier, vol. 244(1), pages 3-12.
    2. M Diaby & A L Nsakanda, 2006. "Large-scale capacitated part-routing in the presence of process and routing flexibilities and setup costs," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(9), pages 1100-1112, September.
    3. Ogbe, Emmanuel & Li, Xiang, 2017. "A new cross decomposition method for stochastic mixed-integer linear programming," European Journal of Operational Research, Elsevier, vol. 256(2), pages 487-499.
    4. Mutsunori Yagiura & Toshihide Ibaraki & Fred Glover, 2004. "An Ejection Chain Approach for the Generalized Assignment Problem," INFORMS Journal on Computing, INFORMS, vol. 16(2), pages 133-151, May.
    5. Weijun Xie & Yanfeng Ouyang & Sze Chun Wong, 2016. "Reliable Location-Routing Design Under Probabilistic Facility Disruptions," Transportation Science, INFORMS, vol. 50(3), pages 1128-1138, August.
    6. Shangyao Yan & Chun-Ying Chen & Chuan-Che Wu, 2012. "Solution methods for the taxi pooling problem," Transportation, Springer, vol. 39(3), pages 723-748, May.
    7. Chou, Chang-Chi & Chiang, Wen-Chu & Chen, Albert Y., 2022. "Emergency medical response in mass casualty incidents considering the traffic congestions in proximity on-site and hospital delays," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 158(C).
    8. Keliang Wang & Leonardo Lozano & Carlos Cardonha & David Bergman, 2023. "Optimizing over an Ensemble of Trained Neural Networks," INFORMS Journal on Computing, INFORMS, vol. 35(3), pages 652-674, May.
    9. Ibrahim Muter & Tevfik Aytekin, 2017. "Incorporating Aggregate Diversity in Recommender Systems Using Scalable Optimization Approaches," INFORMS Journal on Computing, INFORMS, vol. 29(3), pages 405-421, August.
    10. Alexandre Belloni & Mitchell J. Lovett & William Boulding & Richard Staelin, 2012. "Optimal Admission and Scholarship Decisions: Choosing Customized Marketing Offers to Attract a Desirable Mix of Customers," Marketing Science, INFORMS, vol. 31(4), pages 621-636, July.
    11. Arabatzis, Garyfallos & Petridis, Konstantinos & Galatsidas, Spyros & Ioannou, Konstantinos, 2013. "A demand scenario based fuelwood supply chain: A conceptual model," Renewable and Sustainable Energy Reviews, Elsevier, vol. 25(C), pages 687-697.
    12. Mazzola, Joseph B. & Neebe, Alan W., 1999. "Lagrangian-relaxation-based solution procedures for a multiproduct capacitated facility location problem with choice of facility type," European Journal of Operational Research, Elsevier, vol. 115(2), pages 285-299, June.
    13. Kroon, Leo G. & Salomon, Marc & Van Wassenhove, Luk N., 1995. "Exact and approximation algorithms for the operational fixed interval scheduling problem," European Journal of Operational Research, Elsevier, vol. 82(1), pages 190-205, April.
    14. Imai, Akio & Nishimura, Etsuko & Current, John, 2007. "A Lagrangian relaxation-based heuristic for the vehicle routing with full container load," European Journal of Operational Research, Elsevier, vol. 176(1), pages 87-105, January.
    15. Martinhon, Carlos & Lucena, Abilio & Maculan, Nelson, 2004. "Stronger K-tree relaxations for the vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 158(1), pages 56-71, October.
    16. Nadjib Brahimi & Stéphane Dauzère-Pérès & Najib M. Najid, 2006. "Capacitated Multi-Item Lot-Sizing Problems with Time Windows," Operations Research, INFORMS, vol. 54(5), pages 951-967, October.
    17. Lei, Chao & Ouyang, Yanfeng, 2018. "Continuous approximation for demand balancing in solving large-scale one-commodity pickup and delivery problems," Transportation Research Part B: Methodological, Elsevier, vol. 109(C), pages 90-109.
    18. Gaudioso, Manlio & Monaco, Maria Flavia & Sammarra, Marcello, 2021. "A Lagrangian heuristics for the truck scheduling problem in multi-door, multi-product Cross-Docking with constant processing time," Omega, Elsevier, vol. 101(C).
    19. Weiner, Jake & Ernst, Andreas T. & Li, Xiaodong & Sun, Yuan & Deb, Kalyanmoy, 2021. "Solving the maximum edge disjoint path problem using a modified Lagrangian particle swarm optimisation hybrid," European Journal of Operational Research, Elsevier, vol. 293(3), pages 847-862.
    20. Zhang, Chuqian & Wan, Yat-wah & Liu, Jiyin & Linn, Richard J., 2002. "Dynamic crane deployment in container storage yards," Transportation Research Part B: Methodological, Elsevier, vol. 36(6), pages 537-555, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pal:jorsoc:v:54:y:2003:i:4:d:10.1057_palgrave.jors.2601489. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.palgrave-journals.com/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.