Intelligently Routing Underwater Wireless Sensor Networks: A Survey,ERICDATA高等教育知識庫
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篇名
Intelligently Routing Underwater Wireless Sensor Networks: A Survey
並列篇名
Intelligently Routing Underwater Wireless Sensor Networks: A Survey
作者 Chaoxing RenYun LiXuejun WangLing Xia LiaoRoy Xiaorong Lai
英文摘要
Current marine scientific research faces a big challenge in accurately and timely collecting marine data due to the highly dynamic underwater environment. Underwater Wireless Sensor Networking (UWSN) systems with intelligent routing approaches are a way to rise to this challenge as the rapid development of Artificial Intelligence (AI) technologies. Unlike traditional routing approaches driven by mathematical models, the ones underwater are intelligent and data driven, which better adapt to the dynamic underwater environment and are able to optimize various performance indicators. This paper reviews the state of arts of applying AI technologies in routing UWSN systems. It divides the routing approaches for UWSN systems into non-cross-layer and cross-layer based. Cross-layer based approaches can be further grouped into traditional cross-layer and intelligent cross-layer approaches, as AI technologies can help data sharing among layers in UWSN systems. This paper focuses on the intelligent cross-layer routing approaches and discusses them according to the type of machine learning algorithms applied. Challenges and some open issues in intelligently routing UWSN systems are also provided. To the best of our knowledge, this work is the first effort on summarizing the challenges, algorithms, and issues in routing UWSN systems intelligently.
起訖頁 1635-1648
關鍵詞 Routing algorithmsEvolutionary algorithmsSupervised learningReinforcement learningUnderwater wireless sensor networks
刊名 網際網路技術學刊  
期數 202112 (22:7期)
出版單位 台灣學術網路管理委員會
DOI 10.53106/160792642021122207016  複製DOI
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