基于复杂网络理论的大规模无线传感器网络节能容错进化新模型

Xiaobo Tan, Ji Tang, Liting Yu, Jialu Wang
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引用次数: 1

摘要

本文基于复杂网络理论,提出了一种新的大规模无线传感器网络节能容错进化模型。在进化模型中,不仅考虑了每个节点的剩余能量,而且引入了链路约束,使得整个网络的能量消耗更加均衡。在进化模型中引入优先依附和随机依附,在一定程度上保持网络无标度特性的同时,降低了高度节点的比例。理论分析表明,新模型是对BA模型的扩展,是BA模型与随机模型的混合模型。仿真结果表明,当随机概率值接近0.2时,EFEM在保持无标度网络特性的同时具有较好的随机网络特性,有助于构建大规模wsn的高生存能力网络。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A New Energy-Efficient and Fault-Tolerant Evolution Model for Large-Scale Wireless Sensor Networks Based on Complex Network Theory
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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