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Bio-inspired routing protocol for WSN-based smart grid applications in the context of Industry 4.0

Faheem, M. and Butt, R. A. and Raza, B. and Ashraf, M. W. and Begum, Seema and Ngadi, Md. A. and Gungor, V. C. (2019) Bio-inspired routing protocol for WSN-based smart grid applications in the context of Industry 4.0. Transactions on Emerging Telecommunications Technologies, 30 (8). pp. 1-24. ISSN 2161-5748

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Official URL: http://dx.doi.org/10.1002/ett.3503


Recently, the advences of Industry 4.0 have paved the way for a systematical deployment of the smart grid (SG) to manage continuously growing energy demand of the 21st century. This even allows the fourth stage of the industrial revolution in the power sector, which is known as the smart grid industry (SGI) 4.0. In SGI 4.0, the industrial wireless sensor networks (WSNs) and the Internet of Things are envisioned as key promising communication technologies for monitoring various SG applications due to their large-scale coverage, fault tolerance characteristics, and cost reduction. However, highly dynamic nature of the SG environments brings several unique challenges caused by systems and operating devices. This results in hampering the quality-of-service communication requirements for WSNs-based SG applications. In SGI 4.0, the routing infrastructure not only requires a reliable but also fulfills the communication requirements of diverse SG applications. Thus, a sophisticated, reliable and QoS-aware multi-hop communications network architecture enabling a real-time exchange of data for various WSNs-based SG applications is essential in SGI 4.0. Hence, this paper proposes a novel bio-inspired self-optimized butterfly mating optimization-based data gathering routing scheme called Self-optimized Intelligent routing protocol (SIRP) for WSNs-based SG applications. The extensive simulations reveal that the proposed scheme achieves its defined goals compared to existing routing schemes designed for WSNs-based applications.

Item Type:Article
Uncontrolled Keywords:communication technologies, extensive simulations, industrial revolutions
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
ID Code:87648
Deposited By: Yanti Mohd Shah
Deposited On:30 Nov 2020 17:06
Last Modified:30 Nov 2020 17:06

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