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A New Energy-Efficient and Fault-Tolerant Evolution Model for Large-Scale Wireless Sensor Networks Based on Complex Network Theory

A New Energy-Efficient and Fault-Tolerant Evolution Model for Large-Scale Wireless Sensor Networks Based on Complex Network Theory

Xiaobo Tan, Ji Tang, Liting Yu, Jialu Wang
Copyright: © 2019 |Volume: 10 |Issue: 3 |Pages: 16
ISSN: 1947-3532|EISSN: 1947-3540|EISBN13: 9781522566861|DOI: 10.4018/IJDST.2019070102
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MLA

Tan, Xiaobo, et al. "A New Energy-Efficient and Fault-Tolerant Evolution Model for Large-Scale Wireless Sensor Networks Based on Complex Network Theory." IJDST vol.10, no.3 2019: pp.21-36. http://doi.org/10.4018/IJDST.2019070102

APA

Tan, X., Tang, J., Yu, L., & Wang, J. (2019). A New Energy-Efficient and Fault-Tolerant Evolution Model for Large-Scale Wireless Sensor Networks Based on Complex Network Theory. International Journal of Distributed Systems and Technologies (IJDST), 10(3), 21-36. http://doi.org/10.4018/IJDST.2019070102

Chicago

Tan, Xiaobo, et al. "A New Energy-Efficient and Fault-Tolerant Evolution Model for Large-Scale Wireless Sensor Networks Based on Complex Network Theory," International Journal of Distributed Systems and Technologies (IJDST) 10, no.3: 21-36. http://doi.org/10.4018/IJDST.2019070102

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Abstract

In this article, the authors present a new novel energy-efficient and fault-tolerant evolution model for large-scale wireless sensor networks based on complex network theory. In the evolution model, not only is the residual energy of each node considered, but also the constraint of links is introduced, which makes the energy consumption of the whole network more balanced. Furthermore, both preferential attachment and random attachment to the evolution model are introduced, which reduces the proportion of the nodes with high degree while keeping scale-free network characteristics to some extent. Theoretical analysis shows that the new model is an extension of the BA model, which is a mixed model between a BA model and a stochastic model. Simulation results show that EFEM has better stochastic network characteristics while keeping scale-free network characteristics if the value of random probability is near 0.2 and it can help to construct a high survivability network for large-scale WSNs.

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