An Energy Efficiency Multi-Level Transmission Strategy based on underwater multimodal communication in UWSNs
Zhao Zhao, Chunfeng Liu, Wenyu Qu, Tao Yu
摘要
This paper discusses the data transmission strategy based on underwater multimodal communication for marine applications in underwater wireless sensor networks (UWSNs). Underwater data required by various applications have different values of information (VoIs) depending on the type and timeliness of events. These data should be transmitted in different time latency according to their VoIs to accommodate the both application requirements and network performance. Our objective is to design a multi-level transmission strategy by using underwater multimodal communication system so that multiple paths with different transmission latency and energy consumption are provided for underwater data in UWSNs. For this purpose, we first define a minimum cost flow (MCF) model for the design of transmission strategy that considers transmission latency, energy efficiency, and transfer load. Then a distributed multilevel transmission strategy EMTS is proposed based on time backoff method for large-scale UWSNs. Finally, we compared the transmission latency, energy efficiency and network lifetime obtained by our EMTS strategy to those of the optimum solution of the MCF model, and a transmission algorithm based on greedy strategy. Although the latency of EMTS is slightly higher than that of other algorithms, our average network lifetime can reach 88.7% of that of the optimum solution of the MCF model.
问问这篇 Paper
问问你的智能体。
Lune 读过与它相关的顶会 Paper,每个回答都会注明依据哪几篇。
相关 Paper
- Minimizing Age of Information for Underwater Optical Wireless Sensor NetworksYu Tian, Lei Wang, Chi Lin, Yang Chi 等INFOCOM 2023 · 被引用 7 次
- Underwater Data Collection Scheme based on LLMsKunhong Ji, Chi Lin, Jiankang Ren, Qiwei Wang 等INFOCOM 2026
- Synergetic Denial-of-Service Attacks and Defense in Underwater Named Data NetworkingYue Li, Yingjian Liu, Yu Wang, Zhongwen Guo 等INFOCOM 2020 · 被引用 10 次
- AquaSaC: A Single Optical Waveform for Underwater Sensing and CommunicationYue Zhang, Peijun Hou, Nan CenINFOCOM 2026
- Reducing AUV Energy Consumption Through Dynamic Sensor Directions Switching via Deep Reinforcement LearningJiawei Liu, Yuanbo Xu, Shanshan Song, Lu JiangAAAI 2025 · 被引用 1 次
