| Title |
Energy-efficient routing paradigm for resource-constrained Internet of Things-based cognitive smart city |
| ID_Doc |
37260 |
| Authors |
Verma, S |
| Title |
Energy-efficient routing paradigm for resource-constrained Internet of Things-based cognitive smart city |
| Year |
2022 |
| Published |
Expert Systems, 39.0, 5 |
| DOI |
10.1111/exsy.12905 |
| Abstract |
The exponential growth in the smart cities and the massive deployment of wireless sensor network-based Internet of Things (IoT) has resulted in generating the humongous data, which needs to be orchestrated. Further, it is observed that the resource-constrained IoT devices act as stumbling block in the successful realization of cognitive smart cities. Hence, there is a high need to manage the data transmission from massive IoT devices and also to enhance the productivity of such devices. To address this issue, in this article, we present energy-efficient routing paradigm for resource-constrained IoT-based cognitive smart city (EI-CSC). We adapt Sooty tern optimization algorithm (STOA) due to its faster convergence and high 'exploration and exploitation' capabilities to perform energy efficient cluster-based routing. We focus primarily on rendering the optimized solution to the cluster head selection problem through STOA. The outcomes of simulation analysis of EI-CSC promises enhanced performance in the context of stability period and network lifetime by 83.4% and 107.7%, 'respectively' as compared to recently proposed 'genetic algorithm and PSO based hybrid clustering algorithm'. |
| Author Keywords |
cluster head; cognitive smart city; IoT; network operational period; resource-constrained; STOA; wireless sensor networks |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED) |
| EID |
WOS:000723827500001 |
| WoS Category |
Computer Science, Artificial Intelligence; Computer Science, Theory & Methods |
| Research Area |
Computer Science |
| PDF |
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