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Energy-Efficient and Blockchain-Enabled Model for Internet of Things (IoT) in Smart Cities

Norah Saleh Alghamdi1,*, Mohammad Ayoub Khan2

1 College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh, 11671, Saudi Arabia
2 College of Computing and Information Technologies, University of Bisha, Bisha, 67714, Saudi Arabia

* Corresponding Author: Norah Saleh Alghamdi. Email: email

Computers, Materials & Continua 2021, 66(3), 2509-2524.


Wireless sensor networks (WSNs) and Internet of Things (IoT) have gained more popularity in recent years as an underlying infrastructure for connected devices and sensors in smart cities. The data generated from these sensors are used by smart cities to strengthen their infrastructure, utilities, and public services. WSNs are suitable for long periods of data acquisition in smart cities. To make the networks of smart cities more reliable for sensitive information, the blockchain mechanism has been proposed. The key issues and challenges of WSNs in smart cities is efficiently scheduling the resources; leading to extending the network lifetime of sensors. In this paper, a linear network coding (LNC) for WSNs with blockchain-enabled IoT devices has been proposed. The consumption of energy is reduced for each node by applying LNC. The efficiency and the reliability of the proposed model are evaluated and compared to those of the existing models. Results from the simulation demonstrate that the proposed model increases the efficiency in terms of the number of live nodes, packet delivery ratio, throughput, and the optimized residual energy compared to other current techniques.


Cite This Article

N. Saleh Alghamdi and M. Ayoub Khan, "Energy-efficient and blockchain-enabled model for internet of things (iot) in smart cities," Computers, Materials & Continua, vol. 66, no.3, pp. 2509–2524, 2021.


cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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