A Detailed Investigation of Wireless Sensor Network Energy Harvesting Schemes to Maximize Lifetime of Sensor Nodes

无线传感器网络 计算机科学 能量收集 能源消耗 无线传感器网络中的密钥分配 节点(物理) 计算机网络 高效能源利用 传感器节点 无线 移动无线传感器网络 能量(信号处理) 实时计算 无线网络 工程类 电气工程 电信 统计 数学 结构工程
作者
Hardeep Singh Dhillon,Kuldip Kumar,Paras Chawla
标识
DOI:10.1109/icct56969.2023.10075842
摘要

For many years, energy harvesting wireless sensor networks (EH-WSNs) development and implementation have been an important and emerging concept in developing technology, considering various EH techniques. This paper includes an investigation of EH-WSN schemes and discussion on various parameters like latency, network size, network density, distance, throughput, lifetime, power consumption, and efficiency related to different energy harvesting schemes. The proposed model demonstrates EH-WSN schemes using different techniques. This paper represents a comparison of various energy harvesting schemes in terms of nodes power consumption. This paper discusses the characteristics and attributes of energy harvesting wireless sensor networks (EH-WSNs). There are several methods to save energy in EH-WSN but they are based on static approach of sensor nodes so we use dynamic approach to minimize energy consumption of wireless sensor nodes. Our primary objective is to maximize lifetime of sensor nodes by minimize the average power consumption. We focus on maximum utilization of node battery, effective distribution of power from the energy harvester to reduce distance between cluster head and source of power. This paper is also highlights the challenges of EH-WSN and technical specifications of various energy harvesting systems. The proposed EH-WSN model replenished the sensor node battery recharging after they become out of service in an efficient way. For this purpose we will use mobile charger which travels to cluster head and provide energy. This article concludes on the compatible EH-WSNs scheme should be used to enhance system efficiency and focus on practical real-life applications of WSN based EH.

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
甜甜圈发布了新的文献求助10
1秒前
甜馨完成签到,获得积分10
4秒前
Chris完成签到 ,获得积分10
4秒前
军军问问张完成签到,获得积分20
5秒前
v0id应助隐形的凡阳采纳,获得10
6秒前
初景发布了新的文献求助10
6秒前
yk完成签到,获得积分20
9秒前
qianlan发布了新的文献求助10
11秒前
汉堡包应助chiweiyoung采纳,获得10
11秒前
ss完成签到,获得积分10
15秒前
quup完成签到,获得积分10
16秒前
传奇3应助nansy采纳,获得10
18秒前
19秒前
共工完成签到 ,获得积分10
19秒前
hrzmlily完成签到,获得积分10
19秒前
renshiq完成签到,获得积分10
20秒前
拼搏霸发布了新的文献求助10
20秒前
研友_VZG7GZ应助quup采纳,获得10
21秒前
22秒前
CodeCraft应助LC2228采纳,获得10
24秒前
ZihaoJin发布了新的文献求助10
24秒前
Cain完成签到,获得积分10
24秒前
28秒前
milo完成签到 ,获得积分10
28秒前
JXDYYZK完成签到,获得积分0
29秒前
Cain发布了新的文献求助10
29秒前
30秒前
mmuoo完成签到,获得积分10
30秒前
woshi123发布了新的文献求助20
30秒前
lhl完成签到,获得积分0
31秒前
33秒前
森sen发布了新的文献求助10
33秒前
李爱国应助ZihaoJin采纳,获得10
34秒前
34秒前
隐形曼青应助qianlan采纳,获得10
36秒前
笨笨的元风完成签到 ,获得积分10
36秒前
muxi完成签到,获得积分20
37秒前
38秒前
39秒前
小白牛完成签到 ,获得积分10
39秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Health Psychology 800
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Electric machines: theory, operating applications, and controls 500
The Analytical and Numerical Solution of Electric and Magnetic Fields 500
When Is Two-Stage Sample Robust Optimization Asymptotically Optimal? 500
Discerning Saints: Moralization of Intrinsic Motivation and Selective Prosociality at Work 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7592932
求助须知:如何正确求助?哪些是违规求助? 9170175
关于积分的说明 19627409
捐赠科研通 7170719
什么是DOI,文献DOI怎么找? 3267529
关于科研通互助平台的介绍 2432418
邀请新用户注册赠送积分活动 2260076