Delay-aware optimized scheduling algorithm for high performance wireless sensor networks
Because of the phenomenal expansion of Internet of Things (IoT) devices around the world, Wireless Sensor Networks (WSN) have become increasingly important among the technical community, and research in this area has been growing exponentially. Researchers have used a variety of WSN technologies to...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2024-01-01
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| Series: | Automatika |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/00051144.2023.2269642 |
| Summary: | Because of the phenomenal expansion of Internet of Things (IoT) devices around the world, Wireless Sensor Networks (WSN) have become increasingly important among the technical community, and research in this area has been growing exponentially. Researchers have used a variety of WSN technologies to address issues such as processing power constraints, bandwidth-limited connections, delays and energy consumption outlines that arise with sensor networks. However, in terms of delay optimization, affordability and effective energy consumption, WSN is the most suitable and alluring technology. This paper uses an Enhanced Scheduling Algorithm (ESA) with a probabilistic approach called Random Classical Game Theory (RCGT) to reduce the delay in WSN. Retransmissions are minimized when ESA and RCGT are used, which improve WSN delay. The idea is to improve the scheduling algorithm by using RCGT to lengthen the lifespan of the entire network. It has been demonstrated that the improved technique outperforms the existing algorithms in terms of throughput, energy consumption, hop count, delay and lifespan ratio. |
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| ISSN: | 0005-1144 1848-3380 |