Evolutionary model of heterogeneous clustering wireless sensor networks based on local world theory
academic paper|更新时间:2024-06-05
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Evolutionary model of heterogeneous clustering wireless sensor networks based on local world theory
Journal on CommunicationsVol. 36, Issue 9, Pages: 204-214(2015)
作者机构:
武汉理工大学 物流工程学院,湖北 武汉 430063
作者简介:
基金信息:
The Twelfth-five National Science Pillar Project(2012BAJ05B07);The National Natural Science Foundation of China(61305110);The Fundamental Research Funds for Central Universities(135118003)
Xiu-wen FU, Wen-feng LI. Evolutionary model of heterogeneous clustering wireless sensor networks based on local world theory[J]. Journal on Communications, 2015, 36(9): 204-214.
DOI:
Xiu-wen FU, Wen-feng LI. Evolutionary model of heterogeneous clustering wireless sensor networks based on local world theory[J]. Journal on Communications, 2015, 36(9): 204-214. DOI: 10.11959/j.issn.1000-436x.2015157.
Evolutionary model of heterogeneous clustering wireless sensor networks based on local world theory
Current research on the scale-free evolutionary model of wireless sensor networks (WSN) treated each network as a homogenous one and does not take into account the evolutionary characteristics of the network in realistic scenarios
thus leading to significant differences between homogenous networks and realistic ones.Therefore
based on local-world theory
a heterogonous evolution model of WSN in relation to cluster-structure
energy-sensitivity and dynamic behavior of WSN (e.g.
failures of nodes and links) was proposed.Compared with previous research results
the proposed model is closer to reality.By using the mean-field theory
the scale-free feature is demonstrated.Moreover
by studying the impacts of topology growth on error tolerance of the network
it is proved that enlarging the size of the local-world and enhancing the upper limit of de-gree is able to improve the network performance in terms of error-tolerance
while an increase in the cluster proportion and deletion probability led to the degradation of the network error tolerance.
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