Effective Implementation of Energy Aware Polarization Diversity for IoT Networks Using Eigenvector Centrality
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The Internet of Things (IoT) is one the most promising area of applications for complex networks since we know that both the efficiency and fidelity of information transmission rely critically on our understanding of network structure. While antenna diversity schemes improve reliability and capacity for point-to-point links of an IoT network that employs multi-polarized antennas, it is currently unclear how implementation should depend on the network structure of the IoT and what impact structure-dependent implementations will have on the energy consumption of IoT devices. We propose an antenna diversity scheme that leverages local network structure and a distributed calculation of centrality to reduce power consumption by 13% when compared to standard selection diversity technique. The proposed approach exploits distributed eigenvector centrality to identify the most influential nodes based on data flow and then limits their antenna switching frequency proportionally to their centrality. Our results also demonstrate that by taking routers’ centrality metric into account, a network can reduce antenna switching frequency by 17% while ensuring approximately 99% packet delivery rate. More broadly, this study highlights how network science can contribute to the development of efficient IoT devices.
KeywordsInternet of Things Centrality Applied network science Network analysis
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