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Blockchain Enabled Energy Efficient Red Deer Algorithm based Clustering Protocol for Pervasive Wireless Sensor Networks
Sustainable Computing: Informatics and Systems ( IF 4.5 ) Pub Date : 2020-10-19 , DOI: 10.1016/j.suscom.2020.100464
Gia Nhu Nguyen , Nin Ho Le Viet , A. Francis Saviour Devaraj , R. Gobi , K. Shankar

Energy efficiency and security are considered as important issues in the design of pervasive wireless networks. Since the nodes in pervasive wireless networks are battery-operated, it becomes essential to develop an energy-efficient method to minimize energy consumption and prolong the network lifetime. This paper presents new energy-efficient and secure clustering based data transmission in pervasive wireless networks using red deer algorithm (RDA) based clustering technique with blockchain enabled secured data transmission, named as RDAC-BC. The proposed RDAC-BC technique undergoes node initialization and performs the clustering process using the RDAC technique. The clustering technique performs cluster head (CH) selection and cluster construction process is carried out. Once the CHs are chosen, blockchain enabled secure data transmission takes place among cluster members (CMs) as well as CHs. The application of RDAC and blockchain technology helps to achieve energy efficiency and security. The experimental validation of the RDAC-BC technique is assessed under several aspects and the results are compared with existing methods. The obtained results ensured that the RDAC-BC technique has shown superior results interms of energy, network lifetime, packet delivery ratio (PDR), and throughput.



中文翻译:

普适无线传感器网络中基于区块链的节能马鹿算法的聚类协议

能源效率和安全性被认为是普遍无线网络设计中的重要问题。由于普及无线网络中的节点都是电池供电的,因此开发一种节能方法以最小化能耗并延长网络寿命变得至关重要。本文提出了一种新的基于节能和安全聚类的普遍无线网络中的数据传输方法,该方法使用基于Red Deer算法(RDA)的聚类技术和具有区块链的安全数据传输,称为RDAC-BC。提出的RDAC-BC技术经过节点初始化,并使用RDAC技术执行聚类过程。群集技术执行群集头(CH)选择,并执行群集构建过程。一旦选择了CH,启用区块链的安全数据传输在集群成员(CM)和CH之间进行。RDAC和区块链技术的应用有助于实现能源效率和安全性。从多个方面评估了RDAC-BC技术的实验验证,并将结果与​​现有方法进行了比较。所获得的结果确保了RDAC-BC技术在能量,网络寿命,数据包传送率(PDR)和吞吐量方面均显示出优异的结果。

更新日期:2020-10-30
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