IEDA-HGEO: Improved Energy Efficient with Clustering-Based Data Aggregation and Transmission Protocol for Underwater Wireless Sensor Networks

被引:9
作者
Joshi, Shubham [1 ]
Anithaashri, T. P. [2 ]
Rastogi, Ravi [3 ]
Choudhary, Gaurav [4 ]
Dragoni, Nicola [4 ]
机构
[1] SVKMS NMIMS Mukesh Patel Sch Technol Management &, Dept Comp Engn, Shirpur 425405, Maharashtra, India
[2] Saveetha Inst Med & Tech Sci, Saveetha Sch Engn, Inst Comp Sci & Engn, Chennai 602105, Tamilnadu, India
[3] Koneru Lakshmaiah Educ Fdn, Dept CSE, Vaddeswaram 522302, Andhra Pradesh, India
[4] Tech Univ Denmark DTU, Dept Appl Math & Comp Sci, DTU Compute, DK-2800 Kongens Lyngby, Denmark
基金
欧盟地平线“2020”;
关键词
UWSN; clustering; multi-hop; energy consumption; SCHEME; MODEL;
D O I
10.3390/en16010353
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
With the emerging technology in underwater wireless sensor networks (UWSN), many researchers are undergoing this field since it cannot maintain the batteries and recharge them manually. Network duration should be taken into account because they can easily be recharged by a non-conventional resource like solar energy. When coming to the data collection process, clustering is an effective method to construct vitality effective UWSNs. The clustering properties of UWSNs differ from those of terrestrial wireless sensor networks (TWSNs) due to the sparse deployment of nodes as well as the dynamic nature of the channel. This paper proposes improved efficient data aggregation in a Hexagonal grid with energy optimization (IEDA-HGEO) protocol for effective data transmission with an optimal clustering process. It is further compared with (ERPR)-R-2 n energy-efficient routing protocol and EGRC (Energy-efficiency Grid Routing based on 3D Cubes). The three techniques mentioned above are specifically examined for their applicability to underwater communication, and their performance is compared in terms of energy consumption, efficiency, throughput, packet delivery ratio, and delay. The proposed method achieved the following metrics: delay 41%, energy consumption 48%, efficiency 95%, throughput 95%, and PDR 92%.
引用
收藏
页数:13
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