TY - JOUR
T1 - Optimizing Sensor Deployment for Target Coverage in UASNs
T2 - An LLM-Enhanced Greedy Approach
AU - Liu, Jun
AU - Zhang, Tong
AU - Li, Hanrui
N1 - Publisher Copyright:
© 1997-2012 IEEE.
PY - 2026
Y1 - 2026
N2 - This letter investigates target coverage in three-dimensional underwater acoustic sensor networks with irregular target distributions. An improved greedy-backtracking deployment algorithm is proposed, where a large language model acts as a meta-controller to generate scenario-specific candidate filtering, target prioritization, and backtracking-depth rules. A relay-based compensation step handles isolated targets, followed by redundancy removal. Simulations show that the proposed IG-LGO approach reduces the number of deployed nodes and improves coverage efficiency compared with greedy and antcolony baselines.
AB - This letter investigates target coverage in three-dimensional underwater acoustic sensor networks with irregular target distributions. An improved greedy-backtracking deployment algorithm is proposed, where a large language model acts as a meta-controller to generate scenario-specific candidate filtering, target prioritization, and backtracking-depth rules. A relay-based compensation step handles isolated targets, followed by redundancy removal. Simulations show that the proposed IG-LGO approach reduces the number of deployed nodes and improves coverage efficiency compared with greedy and antcolony baselines.
KW - Large language model
KW - Sensor deployment
KW - Target coverage
KW - Underwater acoustic sensor networks
UR - https://www.scopus.com/pages/publications/105051490683
U2 - 10.1109/LCOMM.2026.3736593
DO - 10.1109/LCOMM.2026.3736593
M3 - 文章
AN - SCOPUS:105051490683
SN - 1089-7798
JO - IEEE Communications Letters
JF - IEEE Communications Letters
ER -