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Optimal topologies for maximizing network transmission capacity

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  • Chen, Zhenhao
  • Wu, Jiajing
  • Rong, Zhihai
  • Tse, Chi K.

Abstract

It has been widely demonstrated that the structure of a network is a major factor that affects its traffic dynamics. In this work, we try to identify the optimal topologies for maximizing the network transmission capacity, as well as to build a clear relationship between structural features of a network and the transmission performance in terms of traffic delivery. We propose an approach for designing optimal network topologies against traffic congestion by link rewiring and apply them on the Barabási–Albert scale-free, static scale-free and Internet Autonomous System-level networks. Furthermore, we analyze the optimized networks using complex network parameters that characterize the structure of networks, and our simulation results suggest that an optimal network for traffic transmission is more likely to have a core–periphery structure. However, assortative mixing and the rich-club phenomenon may have negative impacts on network performance. Based on the observations of the optimized networks, we propose an efficient method to improve the transmission capacity of large-scale networks.

Suggested Citation

  • Chen, Zhenhao & Wu, Jiajing & Rong, Zhihai & Tse, Chi K., 2018. "Optimal topologies for maximizing network transmission capacity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 495(C), pages 191-201.
    • Handle: RePEc:eee:phsmap:v:495:y:2018:i:c:p:191-201
    DOI: 10.1016/j.physa.2017.12.084
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    References listed on IDEAS

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    1. Huang, Wei & Chow, Tommy W.S., 2010. "Network topological optimization for packet routing using multi-objective simulated annealing method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(4), pages 871-880.
    2. Zhongyuan Jiang & Mangui Liang & Dongchao Guo, 2011. "Enhancing Network Performance By Edge Addition," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 22(11), pages 1211-1226.
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    4. Pu, Cun-Lai & Zhou, Si-Yuan & Wang, Kai & Zhang, Yi-Feng & Pei, Wen-Jiang, 2012. "Efficient and robust routing on scale-free networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(3), pages 866-871.
    5. Jiang, Zhong-Yuan & Ma, Jian-Feng & Shen, Yu-Long & Zeng, Yong, 2016. "Effects of link-orientation methods on robustness against cascading failures in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 457(C), pages 1-7.
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    Cited by:

    1. Wu, Taocheng & Wu, Jiajing & You, Wei, 2018. "Optimizing robustness of complex networks with heterogeneous node functions based on the Memetic Algorithm," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 511(C), pages 143-153.
    2. Wang, Jin-Fa & He, Xuan & Si, Shuai-Zong & Zhao, Hai & Zheng, Chunyang & Yu, Hao, 2019. "Using complex network theory for temporal locality in network traffic flows," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 722-736.
    3. Kumari, Suchi & Saroha, Abhishek & Singh, Anurag, 2020. "Efficient edge rewiring strategies for enhancement in network capacity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    4. Zhang, Junfeng & Ma, Jinlong & Li, Hui-Jia, 2022. "An efficient link closing strategy for improving traffic capacity on scale-free networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).

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