Swarm-Intelligence-Based Routing and Wavelength Assignment in Optical Satellite Networks

Yuanfeng Li, Qi Zhang*, Haipeng Yao*, Ran Gao, Xiangjun Xin, Feng Tian, Qinghua Tian, Weiying Feng, Dong Chen

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)

Abstract

Routing and wavelength assignment (RWA) determine the quality of service (QoS) such as blocking probability and delay in wavelength division multiplexing (WDM) satellite optical network, whose topology is time-varying due to the high-speed mobility between satellite orbits. This article introduces an ant colony optimization with adaptive load balance small window strategy under hop number loose constraint (ACO-ALB-SWS-HNLC) which has highly robust to solving the RWA issue in the dynamic topology of the satellite optical network. In our proposed algorithm, an adaptive small window strategy and hop number loose constraint are proposed to improve the convergence speed and reduce the number of node hops by limiting its convergence area adaptively through the load in the window. The pheromone evaporation rate is controlled by wavelength usage between the links in the window to balance the load. The result shows that, compared to other ACO algorithms, ACO-ALB-SWS-HNLC can effectively reduce blocking probability. In addition, good convergence speed and communication delay are maintained as well.

Original languageEnglish
Pages (from-to)1303-1319
Number of pages17
JournalIEEE Transactions on Network Science and Engineering
Volume11
Issue number1
DOIs
Publication statusPublished - 1 Jan 2024

Keywords

  • Ant colony optimization
  • optical satellite network
  • routing and wavelength assignment
  • swarm intelligence

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Li, Y., Zhang, Q., Yao, H., Gao, R., Xin, X., Tian, F., Tian, Q., Feng, W., & Chen, D. (2024). Swarm-Intelligence-Based Routing and Wavelength Assignment in Optical Satellite Networks. IEEE Transactions on Network Science and Engineering, 11(1), 1303-1319. https://doi.org/10.1109/TNSE.2023.3321879