亲爱的研友该休息了!由于当前在线用户较少,发布求助请尽量完整的填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!身体可是革命的本钱,早点休息,好梦!

Energy-Efficient Guiding-Network-Based Routing for Underwater Wireless Sensor Networks

计算机科学 计算机网络 路由协议 静态路由 动态源路由 链路状态路由协议 区域路由协议 无线路由协议 多路径等成本路由 地理路由 分布式计算 网络数据包
作者
Zhixin Liu,Xiaocao Jin,Yi Yang,Kai Ma,Xinping Guan
出处
期刊:IEEE Internet of Things Journal [Institute of Electrical and Electronics Engineers]
卷期号:9 (21): 21702-21711 被引量:31
标识
DOI:10.1109/jiot.2022.3183128
摘要

With the increasing underwater applications, underwater wireless sensor networks (UWSNs) have become a research hotspot. Routing protocols used to keep network connectivity and reliable transmission are essential in UWSNs. Due to the specific limitations in UWSNs, such as serious ocean interference, high propagation latency, and dynamic network topology, it is challenging to balance multiple performances, such as real timeness and energy efficiency in a routing protocol. To this end, this article proposes a localization-free routing scheme, termed energy-efficient guiding-network-based routing (EEGNBR) protocol, to provide a time saving and reliable routing for UWSNs, which is a good choice for applications characterized by intermittent connectivity. For reducing the network delay, EEGNBR cites the advantageous distance-vector mechanism and establishes a guiding network to provide underwater sensor nodes with the shortest route (minimum hop counts) toward the sinks. Moreover, EEGNBR innovatively replaces the waiting mechanism used in traditional opportunistic routing with a novel data forwarding mechanism named concurrent working mechanism, which could greatly reduce the forwarding delay while guaranteeing reliable routing. In order to ensure routing reliability as well as avoid duplicate transmission, the forwarding protection mechanism is adopted to save energy consumption and extend the service life of the network. Simulation results show that EEGNBR performs significantly better than some classical related protocols in terms of network delay while maintaining comparable or even better energy consumption and packet delivery ratio.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
2秒前
可爱的函函应助VDC采纳,获得10
9秒前
10秒前
hxd发布了新的文献求助10
15秒前
浦肯野举报否定之否定求助涉嫌违规
24秒前
26秒前
31秒前
38秒前
VDC发布了新的文献求助10
44秒前
汉堡包应助科研通管家采纳,获得10
47秒前
50秒前
橙橙完成签到,获得积分10
53秒前
54秒前
cassie完成签到,获得积分10
55秒前
cassie发布了新的文献求助10
59秒前
caca完成签到,获得积分10
1分钟前
KKIII完成签到,获得积分10
1分钟前
香蕉觅云应助無烏雾采纳,获得10
1分钟前
科研通AI40应助虚幻的不评采纳,获得10
1分钟前
1分钟前
qpp发布了新的文献求助10
1分钟前
DHL完成签到,获得积分10
1分钟前
1分钟前
qpp完成签到,获得积分10
1分钟前
1分钟前
無烏雾发布了新的文献求助10
1分钟前
iorpi发布了新的文献求助10
2分钟前
浦肯野举报否定之否定求助涉嫌违规
2分钟前
Kashing完成签到,获得积分10
2分钟前
2分钟前
2分钟前
manchang完成签到 ,获得积分10
2分钟前
领导范儿应助Ade阿德采纳,获得10
2分钟前
2分钟前
NexusExplorer应助科研通管家采纳,获得10
2分钟前
2分钟前
丰富寒风完成签到,获得积分20
2分钟前
VDC发布了新的文献求助30
3分钟前
慕斯完成签到,获得积分10
3分钟前
3分钟前
高分求助中
Genetics: From Genes to Genomes 3000
Production Logging: Theoretical and Interpretive Elements 2500
Continuum thermodynamics and material modelling 2000
Healthcare Finance: Modern Financial Analysis for Accelerating Biomedical Innovation 2000
Applications of Emerging Nanomaterials and Nanotechnology 1111
Les Mantodea de Guyane Insecta, Polyneoptera 1000
Diabetes: miniguías Asklepios 800
热门求助领域 (近24小时)
化学 医学 材料科学 生物 工程类 有机化学 生物化学 纳米技术 内科学 物理 化学工程 计算机科学 复合材料 基因 遗传学 物理化学 催化作用 细胞生物学 免疫学 电极
热门帖子
关注 科研通微信公众号,转发送积分 3471419
求助须知:如何正确求助?哪些是违规求助? 3064459
关于积分的说明 9088179
捐赠科研通 2755113
什么是DOI,文献DOI怎么找? 1511775
邀请新用户注册赠送积分活动 698575
科研通“疑难数据库(出版商)”最低求助积分说明 698460