Journal
COMPUTER NETWORKS
Volume 238, Issue -, Pages -Publisher
ELSEVIER
DOI: 10.1016/j.comnet.2023.110102
Keywords
Satellite network; Parallel simulation; Resource assessment; Topology partitioning
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This paper proposes a method based on a parallel network simulation architecture to improve the simulation efficiency of satellite networks. By effectively partitioning the network topology and using algorithms such as resource assessment and load balancing, the simulation performance is enhanced. Experimental results demonstrate the effectiveness of this method.
Satellite Internet, as an important component of the integrated space-ground information network, is a hot research hotspot nowadays. Many scholars have undertaken research in the areas of constellation networking design, network protocol design, and communication performance assessment, and their main research tool is software simulation. Traditional stand-alone network simulation simulators based on OPNET or NS3 are constrained in the simulation efficiency of mega satellite networks because of the limitations of computer hardware conditions and software performance. Based on the above characteristics, we propose a parallel network simulation architecture based on low correlation between different areas of the global satellite network, and in order to improve the parallel network simulation performance, the network topology needs to be divided effectively. Therefore, firstly we consider CPU and memory resource consumption as a measure of topology partitioning performance indicators, propose a resource assessment algorithm and use the result of this assessment as the topology partitioning optimization objective; secondly, we propose a load balancing based intelligent topology partitioning algorithm (LBTP); thirdly, we propose a time slice algorithm (TSA) for parallel simulation in each time cycle. To demonstrate the algorithm proposed in this paper, we built a simulation platform based on the combination of STK (Satellite Tool Kit), OPNET and Proxmox VE, and experimentally verified that the proposed architecture and algorithm significantly improve the simulation efficiency.
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