ABSTRACT The growing need for efficient communication underwater requires energy‐sensitive data compression and edge processing optimization methods for energy‐limited underwater Internet of Things (IoT) networks. The study applies AECO (adaptive energy‐constrained optimization) to optimize compression ratios, edge processing, and transmission power in real‐time network conditions. To reduce the energy cost and maintain data fidelity, AECO employs adaptive wavelet‐based compression, lightweight convolutional filters, and feedback‐based transmission power control. The results of the experiment show that AECO is more efficient and less latent compared to baseline methods; therefore, AECO can be a good solution to the next generation of underwater IoT networks.
Sundaram et al. (Thu,) studied this question.
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