TY - JOUR
T1 - Aqua-Sim Fourth Generation
T2 - Toward General and Intelligent Simulation for Underwater Acoustic Networks
AU - Guo, Jiani
AU - Song, Shanshan
AU - Chen, Hao
AU - Huangfu, Bingwen
AU - Liu, Jun
AU - Cui, Jun Hong
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2025
Y1 - 2025
N2 - Simulators are essential to troubleshoot and optimize Underwater Acoustic Network (UAN) schemes (network protocols and communication technologies) before real field experiments. However, due to programming differences between the above two contents, most existing simulators concentrate on one while weakening the other, leading to nongeneric simulations and biased performance results. Moreover, novel UAN schemes increasingly integrate Artificial Intelligence (AI) techniques, yet existing simulators lack support for necessary AI frameworks, failing to train and evaluate these intelligent methods. On the other hand, these novel schemes consider more UAN characteristics involving more complex parameter configurations, which also challenge simulators in flexibility and fineness. To keep abreast of advances in UANs, we propose the Fourth Generation (FG) network simulator-3 (ns-3)-based simulator Aqua-Sim FG, enhancing the general and intelligent simulation ability. On the basis of retaining previous generations’ functions, we design a new general architecture, which is compatible with various programming languages, including MATLAB, C++, and Python. In this way, Aqua-Sim FG provides a general environment to simulate communication technologies, network protocols, and AI models simultaneously. In addition, we expand six new features from node and communication levels by considering the latest UAN methods’ requirements, which enhances the simulation flexibility and fineness of Aqua-Sim FG. Experimental results show that Aqua-Sim FG can simulate UANs’ performance realistically, reflect intelligent methods’ problems in real-ocean scenarios, and provide more effective troubleshooting and optimization for actual UANs.
AB - Simulators are essential to troubleshoot and optimize Underwater Acoustic Network (UAN) schemes (network protocols and communication technologies) before real field experiments. However, due to programming differences between the above two contents, most existing simulators concentrate on one while weakening the other, leading to nongeneric simulations and biased performance results. Moreover, novel UAN schemes increasingly integrate Artificial Intelligence (AI) techniques, yet existing simulators lack support for necessary AI frameworks, failing to train and evaluate these intelligent methods. On the other hand, these novel schemes consider more UAN characteristics involving more complex parameter configurations, which also challenge simulators in flexibility and fineness. To keep abreast of advances in UANs, we propose the Fourth Generation (FG) network simulator-3 (ns-3)-based simulator Aqua-Sim FG, enhancing the general and intelligent simulation ability. On the basis of retaining previous generations’ functions, we design a new general architecture, which is compatible with various programming languages, including MATLAB, C++, and Python. In this way, Aqua-Sim FG provides a general environment to simulate communication technologies, network protocols, and AI models simultaneously. In addition, we expand six new features from node and communication levels by considering the latest UAN methods’ requirements, which enhances the simulation flexibility and fineness of Aqua-Sim FG. Experimental results show that Aqua-Sim FG can simulate UANs’ performance realistically, reflect intelligent methods’ problems in real-ocean scenarios, and provide more effective troubleshooting and optimization for actual UANs.
KW - Network troubleshooting and optimization
KW - underwater acoustic network (UAN)
KW - underwater network simulation
UR - https://www.scopus.com/pages/publications/105006593286
U2 - 10.1109/JIOT.2025.3571022
DO - 10.1109/JIOT.2025.3571022
M3 - 文章
AN - SCOPUS:105006593286
SN - 2327-4662
VL - 12
SP - 30203
EP - 30214
JO - IEEE Internet of Things Journal
JF - IEEE Internet of Things Journal
IS - 15
ER -