Improve Energy Consumption and Signal Transmission Quality of Routings in Wireless Sensor Networks
| Autor: | Yuan-Hui Yeh, Cheng-Feng Hu, Neal N. Xiong, Wei-Chang Yeh, Chia-Ling Huang, Yunzhi Jiang |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
General Computer Science
business.industry Distributed computing Reliability (computer networking) 020208 electrical & electronic engineering General Engineering Particle swarm optimization 020206 networking & telecommunications Ranging 02 engineering and technology Energy consumption algorithms Smart grid routing energy consumption 0202 electrical engineering electronic engineering information engineering network reliability Wireless General Materials Science lcsh:Electrical engineering. Electronics. Nuclear engineering Routing (electronic design automation) business lcsh:TK1-9971 Wireless sensor network |
| Zdroj: | IEEE Access, Vol 8, Pp 198254-198264 (2020) |
| ISSN: | 2169-3536 |
| Popis: | Wireless (smart) sensor networks (WSNs) comprise a myriad of embedded wireless smart sensors. They play a cardinal role in the functioning of many applications, such as the Internet of Things, smart grids, smart production systems, and smart homes, which ultimately render them paramount instruments in the modern age. Recent advances in WSNs have resulted in the rapid development of sensors. However, WSNs will only able to achieve better execution efficiencies if their energy consumption - owing to limited battery life and difficulty of recharging - can be better controlled. Moreover, signal transmission quality determines WSN performance. Hence, two main concerns - energy consumption and signal transmission quality - should be addressed to improve the performance of WSNs. Thus, a new bi-objective simplified swarm optimization algorithm (bSSO) is proposed by employing the concepts of simple routing, SSO, and crowd distance. The performance and applicability of the proposed bSSO using eight different parameter settings are demonstrated through an experiment involving ten WSN benchmarks ranging from 100 to 1000 sensors. The proposed algorithm is then compared with NSGA-II, which is an algorithm widely used to solve multi-objective problems. The results show that the proposed bSSO can successfully achieve the aim of this work. |
| Databáze: | OpenAIRE |
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