Application of Information Transmission Control Strategy Based on Incremental Community Division in IoT Platform
Nowadays, there are usually a huge number of sensors in most of the Internet of Things. In this case, if a large number of nodes in the network transmit information at the same time, the chaotic information transmission control mechanism will seriously reduce the transmission efficiency. Therefore,...
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Veröffentlicht in: | IEEE sensors journal 2021-10, Vol.21 (19), p.21968-21978 |
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Sprache: | eng |
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Zusammenfassung: | Nowadays, there are usually a huge number of sensors in most of the Internet of Things. In this case, if a large number of nodes in the network transmit information at the same time, the chaotic information transmission control mechanism will seriously reduce the transmission efficiency. Therefore, it has always been a key issue to develop a good transmission control mechanism. In order to overcome this problem, this paper proposes a community representation model based on the neighborhood follow relationship. The community depicted by this model is composed of nodes with different roles and the relationships between nodes. By discovering the direct or indirect following relationship between nodes, a group of nodes that follow the same node can be classified as a community. Furthermore, for the evolution of nodes in the network, an incremental neighborhood following algorithm is proposed. It only needs to update the neighborhood follow relationship of related nodes that have changed in the Internet of Things to realize the community structure division in the dynamic network. In this way, closely connected nodes can be divided into the same community. Then through the community to select relay nodes for hierarchical propagation can greatly enhance the efficiency of information transmission in the Internet of Things. Finally, through a comparative experiment with other classic algorithms. We can see that this method has excellent performance in reducing energy consumption and improving information transmission efficiency. |
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ISSN: | 1530-437X 1558-1748 |
DOI: | 10.1109/JSEN.2021.3102683 |