Abstract
The subnetwork architecture and dynamic optimization difficulties of a dynamic heterogeneous network must be investigated in order to handle the rising number of nodes and links. For the difficult challenge of dynamic network topology changing in time order and varied node characteristics of the heterogeneous network, a mathematical model is constructed to represent the motion of the dynamic network. Consider essential constraints such as inter-node visibility and connection, and use the average end-to-end latency in the network as the optimization goal to create an optimization model based on numerous constraints of the network topology. To solve the global optimum topology, an adaptive approach based on ant colony and simulated annealing algorithms is presented. Finally, the Iridium constellation and the Globalstar constellation are used to verify the simulation. The experimental findings show that the suggested technique not only decreases the algorithm's running time and improves its efficiency when compared to previous topology optimization methods, but also solves for a better solution space.
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The authors are grateful to the editor and anonymous reviewers for their suggestions in improving the quality of the paper.
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This paper is supported by: 1. Major Science and Technology Special Project of Sichuan Province, P.R.China (Grant no. 2018GZDZX0006). 2. Major Science and Technology Special Project of Sichuan Province, P.R.China (Grant no. 2018GZDZX0007).
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Zhuo, M., Yang, P., Chen, J., Liu, L., Liu, C. (2022). Adaptive Optimization of Dynamic Heterogeneous Network Topologies: A Simulated Annealing Methodology. In: Sun, X., Zhang, X., Xia, Z., Bertino, E. (eds) Artificial Intelligence and Security. ICAIS 2022. Lecture Notes in Computer Science, vol 13339. Springer, Cham. https://doi.org/10.1007/978-3-031-06788-4_49
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