نوع مقاله : مقاله پژوهشی
نویسندگان
گروه مهندسی کامپیوتر، دانشکده فنی و مهندسی، دانشگاه بین المللی امام خمینی، قزوین، ایران
چکیده
کلیدواژهها
موضوعات
عنوان مقاله [English]
نویسندگان [English]
Underwater wireless sensor networks (UWSNs) face various constraints such as limited node energy, sensor mobility at different depths, and the need for diverse communication methods. These limitations reduce the efficiency of conventional routing algorithms used in other multi-hop wireless networks. In this study, an innovative routing method based on reinforcement learning and generative adversarial neural networks (GANs) is proposed for UWSNs. The proposed approach aims to discover and store optimal data transmission paths within the network. Subsequently, these paths are used to train a deep learning model following the generative adversarial neural network framework, allowing for the generation of new routes. Simulation results demonstrate that the proposed method improves the successful packet delivery rate and extends network lifetime compared to traditional reinforcement learning techniques in UWSNs.
کلیدواژهها [English]
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