An Energy-Efficient Clustering Routing Protocol Based on Data Aggregation for Underwater Acoustic Sensor Networks

被引:3
|
作者
Xiao, Xingxing [1 ,2 ,3 ]
Chi, Cheng [1 ,2 ]
Huang, Haining [1 ,2 ,3 ]
Huang, Jing [1 ,2 ,3 ]
Wang, Wei [1 ,2 ]
机构
[1] Chinese Acad Sci, Inst Acoust, Beijing, Peoples R China
[2] Chinese Acad Sci, Key Lab Sci & Technol Adv Underwater Acoust Signa, Beijing, Peoples R China
[3] Univ Chinese Acad Sci, Beijing, Peoples R China
基金
国家重点研发计划;
关键词
clustering routing protocols; energy efficiency; data aggregation; underwater acoustic sensor networks; K-means; ENHANCED K-MEANS; ALGORITHMS;
D O I
10.1109/IEEECONF38699.2020.9389438
中图分类号
U6 [水路运输]; P75 [海洋工程];
学科分类号
0814 ; 081505 ; 0824 ; 082401 ;
摘要
Since the energy of underwater acoustic sensor nodes is restrained and the replacement of these nodes is difficult, it is important and necessary to design efficient and effective protocols in underwater acoustic sensor networks (UASNs) to prolong the lifetime of UASNs. This paper presents an energy-efficient clustering routing protocol based on data aggregation for UASNs. Clustering routing protocols divide the network into clusters, and there are some cluster member nodes (CMNs) and one cluster head node (CHN) in one cluster. This paper proposes an improved mechanism to elect CHNs and presents a two-level data aggregation at the CMN level and the CHN level. The CMN collects data periodically, reduces the data redundancy and discards the error data before transmitting the data to the CHN. Once the CHN receives the data sent by CMNs, it performs data aggregation using the K-means algorithm and forwards the representative data to the sink node. The use of the K-means algorithm helps to keep the useful information as well as reduce the data size transmitted to the sink node, which improves the energy efficiency significantly. The simulation illustrates that our proposed protocol is more effective in the energy efficiency and the network lifetime compared to other three protocols.
引用
收藏
页数:6
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