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Erschienen in:
27.12.2017
Small Data: Effective Data Based on Big Communication Research in Social Networks
Erschienen in: Wireless Personal Communications | Ausgabe 3/2018
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Abstract
Big data research is difficult because of its complex structure, vast data storage, and unpredictable change. Social network communication involves a significant amount of incomputable data created by wireless devices across the world. Such data can be used to analyze human activities, seek certain patterns using communication data, and predict emergencies. However, most data are effect of human to research our activities. So, recording effective node distribution and investigating the topological structure in communication are particularly important in big data communication. This study establishes a big data communication simulation environment by searching small data and calculating the influence of small data nodes. The experiment shows that 1% of small data can connect 75% of communication nodes and 20% of small data can transmit 80% of data packets.