Secured Protocol with Collaborative IoT-Enabled Sustainable Communication Using Artificial Intelligence Technique

Naveed Islam, Khalid Haseeb, Muhammad Ali and Gwanggil Jeon
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Naveed Islam: Department of Computer Science, Islamia College Peshawar, Peshawar 25000, Pakistan
Khalid Haseeb: Department of Computer Science, Islamia College Peshawar, Peshawar 25000, Pakistan
Muhammad Ali: Institute of Management Sciences (IMSciences) Peshawar, Peshawar 25100, Pakistan
Gwanggil Jeon: Department of Embedded Systems Engineering, Incheon National University, Incheon 22012, Korea

Sustainability, 2022, vol. 14, issue 14, 1-12

Abstract: In recent years, 5G and the Internet of Things (IoT) have been integrated into a variety of applications to support sustainable communication systems. In the presence of intermediate hardware, IoT devices collect the network data and transfer them to cloud technologies. The interconnect machines provide essential information to the connected devices over the Internet. Many solutions have been proposed to address the dynamic and unexpected characteristics of IoT-based networks and to support smart developments. However, more work needs to explore efficient quality-aware data routing for distributed processing. Additionally, to handle the massive amount of data created by smart cities and achieve the transportation objectives for resource restrictions, artificial intelligence (AI)-oriented approaches are necessary. This research proposes a secured protocol with collaborative learning for IoT-enabled sustainable communication using AI techniques. This approach increases systems’ reaction times in critical conditions and also controls the smart functionalities for inter-device communication. Furthermore, fitness computing can help in balancing the contribution of quality-aware metrics to achieve load balancing and efficient energy consumption. To deal with security, IoT communication is broken down into stages, resulting in a more dependable network for unpredictable environments. The simulation results of the proposed protocol have been compared to existing approaches and improved the performance of response time by 17%, energy consumption by 14%, number of re-transmissions by 16%, and computing overhead by 16%, under a varying number of nodes and data packets.

Keywords: artificial intelligence; internet of things; sustainable system; massive data; smart cities (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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