EGCIR: Energy-Aware Graph Clustering and Intelligent Routing Using Supervised System in Wireless Sensor Networks

Tanzila Saba, Khalid Haseeb, Ikram Ud Din, Ahmad Almogren, Ayman Altameem and Suliman Mohamed Fati
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Tanzila Saba: Artificial Intelligence & Data Analytics Lab (AIDA), College of Computer and Information Sciences (CCIS), Prince Sultan University, Riyadh 11586, Saudi Arabia
Khalid Haseeb: Department of Computer Science, Islamia College University, Peshawar 25000, Pakistan
Ikram Ud Din: Department of Information Technology, The University of Haripur, Haripur 22620, Pakistan
Ahmad Almogren: Department of Computer Science, College of Computer and Information Sciences, King Saud University, Riyadh 11633, Saudi Arabia
Ayman Altameem: Department of Natural and Engineering Sciences, College of Applied Studies and Community Services, King Saud University, Riyadh 11543, Saudi Arabia
Suliman Mohamed Fati: Artificial Intelligence & Data Analytics Lab (AIDA), College of Computer and Information Sciences (CCIS), Prince Sultan University, Riyadh 11586, Saudi Arabia

Energies, 2020, vol. 13, issue 16, 1-15

Abstract: In recent times, the field of wireless sensor networks (WSNs) has attained a growing popularity in observing the environment due to its dynamic factors. Sensor data are gathered and forwarded to the base station (BS) through a wireless transmission medium. The data from the BS is further distributed to end-users using the Internet for their post analysis and operations. However, all sensors except the BS have limited constraints in terms of memory, energy and computational resources that degrade the network performance concerning the network lifetime and trustworthy routing. Therefore, improving energy efficiency with reliable and secure transmissions is a valuable debate among researchers for critical applications based on low-powered sensor nodes. In addition, security plays a significant cause to achieve responsible communications among sensors due to their unfixed and variable infrastructures. Keeping in view the above-mentioned issues, this paper presents an energy-aware graph clustering and intelligent routing (EGCIR) using a supervised system for WSNs to balance the energy consumption and load distribution. Moreover, a secure and efficient key distribution in a hierarchy-based mechanism is adopted by the proposed solution to improve the network efficacy in terms of routes and links integrity. The experimental results demonstrated that the EGCIR protocol enhances the network throughput by an average of 14%, packet drop ratio by an average of 50%, energy consumption by an average of 13%, data latency by an average of 30.2% and data breaches by an average of 37.5% than other state-of-the-art protocols.

Keywords: energy efficiency; graph clustering; key distribution; link security; wireless sensor networks (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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