TY - JOUR
T1 - Swarm-Intelligence-Based Routing and Wavelength Assignment in Optical Satellite Networks
AU - Li, Yuanfeng
AU - Zhang, Qi
AU - Yao, Haipeng
AU - Gao, Ran
AU - Xin, Xiangjun
AU - Tian, Feng
AU - Tian, Qinghua
AU - Feng, Weiying
AU - Chen, Dong
N1 - Publisher Copyright:
© 2013 IEEE.
PY - 2024/1/1
Y1 - 2024/1/1
N2 - 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.
AB - 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.
KW - Ant colony optimization
KW - optical satellite network
KW - routing and wavelength assignment
KW - swarm intelligence
UR - http://www.scopus.com/inward/record.url?scp=85174852963&partnerID=8YFLogxK
U2 - 10.1109/TNSE.2023.3321879
DO - 10.1109/TNSE.2023.3321879
M3 - Article
AN - SCOPUS:85174852963
SN - 2327-4697
VL - 11
SP - 1303
EP - 1319
JO - IEEE Transactions on Network Science and Engineering
JF - IEEE Transactions on Network Science and Engineering
IS - 1
ER -