Open Access

ARTICLE

Energy-efficient and Secure Wireless Communication for Telemedicine in IoT

Shital Joshi¹, S. Manimurugan^2,3, Ahamed Aljuhani^2,*, Umar Albalawi², Amer Aljaedi²

1 Department of Computer Science, Oklahoma State University, Oklahoma, USA
2 College of Computing and Information Technology, University of Tabuk, Tabuk, 71491, Saudi Arabia
3 Industrial Innovation and Robotics Center, University of Tabuk, Tabuk, Saudi Arabia

* Corresponding Author: Ahamed Aljuhani. Email:

Computer Systems Science and Engineering 2022, 43(3), 1111-1130. https://doi.org/10.32604/csse.2022.024802

Received 31 October 2021; Accepted 10 December 2021; Issue published 09 May 2022

Abstract

The Internet of Things (IoT) represents a radical shifting paradigm for technological innovations as it can play critical roles in cyberspace applications in various sectors, such as security, monitoring, medical, and environmental sectors, and also in control and industrial applications. The IoT in E-medicine unleashed the design space for new technologies to give instant treatment to patients while also monitoring and tracking health conditions. This research presents a system-level architecture approach for IoT energy efficiency and security. The proposed architecture includes functional components that provide privacy management and system security. Components in the security function group provide secure communications through Multi-Authority Ciphertext-Policy Attributes-Based Encryption (MA-CPABE). Because MA-CPABE is assigned to unlimited devices, presuming that the devices are reliable, the user encodes data with Advanced Encryption Standard (AES) and protects the ABE approach using the solutions of symmetric key. The Johnson’s algorithm with a new computation measure is used to increase network lifetime since an individual sensor node with limited energy represents the inevitable constraints for the broad usage of wireless sensor networks. The optimal route from a source to destination turns out as the cornerstone for longevity of network and its sustainability. To reduce the energy consumption of networks, the evaluation measures consider the node’s residual energy, the number of neighbors, their distance, and the link dependability. The experiment results demonstrate that the proposed model increases network life by about 12.25% (27.73%) compared to Floyd–Warshall’s, Bellman–Ford’s, and Dijkstra’s algorithms, lowering consumption of energy by eliminating the necessity for re-routing the message as a result of connection failure.

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Keywords

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