IDEAS home Printed from https://ideas.repec.org/a/spr/joptap/v206y2025i2d10.1007_s10957-025-02710-8.html
   My bibliography  Save this article

Closed-Form Formulas for Cluster Sizing for Two-Level Hierarchical Networks with Source Routing

Author

Listed:
  • Eric Rosenberg

    (Seton Hall University)

Abstract

In a two-level hierarchical network, nodes are grouped into clusters. A node in one cluster sees the entire topology of that cluster, but only a summarized view of other clusters. With source routing, the source node of a connection does an initial route computation based on its view of the network, and additional route computations are performed as the connection makes its way towards the destination. We study the problem of choosing the number of clusters to minimize the total complexity of all the path computations required to compute a path from a source node to a destination node. We show that, under mild conditions, for all sufficiently large networks two-level hierarchical routing is superior to flat network routing. Utilizing the duality theory of geometric programming, we provide a closed-form solution estimate for the number of clusters to minimize the total routing complexity. We also provide a closed-form expression for a lower bound on the minimal total complexity. We illustrate the modelling assumptions for a variety of networks. Computational results for a range of network sizes and parameters show that our solution estimate yields near-optimal results.

Suggested Citation

  • Eric Rosenberg, 2025. "Closed-Form Formulas for Cluster Sizing for Two-Level Hierarchical Networks with Source Routing," Journal of Optimization Theory and Applications, Springer, vol. 206(2), pages 1-34, August.
  • Handle: RePEc:spr:joptap:v:206:y:2025:i:2:d:10.1007_s10957-025-02710-8
    DOI: 10.1007/s10957-025-02710-8
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10957-025-02710-8
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10957-025-02710-8?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Chaoming Song & Shlomo Havlin & Hernán A. Makse, 2005. "Self-similarity of complex networks," Nature, Nature, vol. 433(7024), pages 392-395, 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. Zhou, Wei-Xing & Jiang, Zhi-Qiang & Sornette, Didier, 2007. "Exploring self-similarity of complex cellular networks: The edge-covering method with simulated annealing and log-periodic sampling," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 375(2), pages 741-752.
    2. Werner, Gerhard, 2013. "Consciousness viewed in the framework of brain phase space dynamics, criticality, and the Renormalization Group," Chaos, Solitons & Fractals, Elsevier, vol. 55(C), pages 3-12.
    3. Blagus, Neli & Šubelj, Lovro & Bajec, Marko, 2012. "Self-similar scaling of density in complex real-world networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(8), pages 2794-2802.
    4. Zhijun SONG & Linjun YU, 2019. "Multifractal features of spatial variation in construction land in Beijing (1985–2015)," Palgrave Communications, Palgrave Macmillan, vol. 5(1), pages 1-15, December.
    5. Yao, Jialing & Sun, Bingbin & Xi, lifeng, 2019. "Fractality of evolving self-similar networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 211-216.
    6. Wijesundera, Isuri & Halgamuge, Malka N. & Nirmalathas, Ampalavanapillai & Nanayakkara, Thrishantha, 2016. "MFPT calculation for random walks in inhomogeneous networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 986-1002.
    7. Lia Papadopoulos & Pablo Blinder & Henrik Ronellenfitsch & Florian Klimm & Eleni Katifori & David Kleinfeld & Danielle S Bassett, 2018. "Comparing two classes of biological distribution systems using network analysis," PLOS Computational Biology, Public Library of Science, vol. 14(9), pages 1-31, September.
    8. Duan, Shuyu & Wen, Tao & Jiang, Wen, 2019. "A new information dimension of complex network based on Rényi entropy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 516(C), pages 529-542.
    9. Ikeda, Nobutoshi, 2020. "Fractal networks induced by movements of random walkers on a tree graph," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 537(C).
    10. Zhou, Ming-Yang & Xiong, Wen-Man & Wu, Xiang-Yang & Zhang, Yu-Xia & Liao, Hao, 2018. "Overlapping influence inspires the selection of multiple spreaders in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 76-83.
    11. Huang, Liang & Zheng, Yu, 2023. "Asymptotic formula on APL of fractal evolving networks generated by Durer Pentagon," Chaos, Solitons & Fractals, Elsevier, vol. 167(C).
    12. Sun, Bingbin & Yao, Jialing & Xi, Lifeng, 2019. "Eigentime identities of fractal sailboat networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 520(C), pages 338-349.
    13. Ortega, José Luis & Aguillo, Isidro F., 2013. "Institutional and country collaboration in an online service of scientific profiles: Google Scholar Citations," Journal of Informetrics, Elsevier, vol. 7(2), pages 394-403.
    14. Ma, Fei & Ouyang, Jinzhi & Shi, Haobin & Pan, Wei & Wang, Ping, 2024. "Type-II Apollonian network: More robust and more efficient Apollonian network," Chaos, Solitons & Fractals, Elsevier, vol. 188(C).
    15. Lu, Qing-Chang & Xu, Peng-Cheng & Zhao, Xiangmo & Zhang, Lei & Li, Xiaoling & Cui, Xin, 2022. "Measuring network interdependency between dependent networks: A supply-demand-based approach," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    16. Lambiotte, R. & Panzarasa, P., 2009. "Communities, knowledge creation, and information diffusion," Journal of Informetrics, Elsevier, vol. 3(3), pages 180-190.
    17. Lazaros K Gallos & Fabricio Q Potiguar & José S Andrade Jr & Hernan A Makse, 2013. "IMDB Network Revisited: Unveiling Fractal and Modular Properties from a Typical Small-World Network," PLOS ONE, Public Library of Science, vol. 8(6), pages 1-8, June.
    18. Li, Jianxuan & Shi, Yingying & Cao, Guangxi, 2018. "Topology structure based on detrended cross-correlation coefficient of exchange rate network of the belt and road countries," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 1140-1151.
    19. Zhang, Qi & Luo, Chuanhai & Li, Meizhu & Deng, Yong & Mahadevan, Sankaran, 2015. "Tsallis information dimension of complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 707-717.
    20. Aldrich, Preston R. & El-Zabet, Jermeen & Hassan, Seerat & Briguglio, Joseph & Aliaj, Enela & Radcliffe, Maria & Mirza, Taha & Comar, Timothy & Nadolski, Jeremy & Huebner, Cynthia D., 2015. "Monte Carlo tests of small-world architecture for coarse-grained networks of the United States railroad and highway transportation systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 438(C), pages 32-39.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:spr:joptap:v:206:y:2025:i:2:d:10.1007_s10957-025-02710-8. 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.springer.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.