Dynamic Clustering-Genetic Secure Energy Awareness Routing To Improve the Performance of Energy Efficient In IoT Cloud

Author:

Karthika E,Mohanapriya S

Abstract

Abstract The Internet of Things (IoT) is one of the emerging technologies that has attracted the attention of researchers in the field of education and industry. The idea behind the Internet of Things is that things and devices are operated on the Internet to achieve some common goals with humans. It serves as a platform for monitoring the collection process, controlling the cyber-global fire world, and collecting data and analyzing data using IoT sensor nodes. Power saving is important for battery-powered devices. The amount of previous work is small, although it has a large tip capacity, especially in terms of battery life and energy efficiency. This regulates the development of IoT a simple and energy efficient routing scheme for war sensor networks. The nodes require an increased lifespan of intelligently transmitted data communications. To conserve the energy of IoT nodes, the Dynamic Clustering-Genetic Secure Energy Awareness Routing Protocol (DC-GSEARP) utilizes clustering, cluster head selection and energy and efficient path calculation for efficient and real-time routing. To accomplish the efficient cluster head selection, to have used Dynamic Clustering algorithm. The proposed DC-GSEARP protocol achieve an improved that can be used to construct an optimal path for energy efficient data transmission for IoT sensor nodes. DC-GSEARP, which uses the integration of clustering supported by short path resolution to provide energy efficient and advanced routing capabilities for IoT, ensures entering a path with lower power consumption and enhanced QoS measurements. The results of the simulations show that the proposed approach can reduce the power consumption of sensor nodes, data packet losses and extend network life.

Publisher

IOP Publishing

Subject

General Medicine

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3