Abstract
Opportunity networks provide a chance to offload the tremendous cellular traffic generated by sharing popular content on mobile networks. Analyzing the content spread characteristics in real opportunity environments can discover important clues for traffic offloading decision making. However, relevant published work is very limited since it is not easy to collect data from real environments. In this study, we elaborate the analysis on the dataset collected from a real opportunity environment formed by the users of Xender, which is one of the leading mobile applications for content sharing. To discover content transmission characteristics, scale, speed, and type analyses are implemented on the dataset. The analysis results show that file transmission has obvious periodicity, that only a very small fraction of files spread widely, and that application files have much higher probability to be popular than other files. We also propose a solution to maximize file spread scales, which is very helpful for forecasting popular files. The experimental results verify the effectiveness and usefulness of our solution.
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Xiao-hong ZHANG, Kai QIAN, Jian-ji REN, Zong-pu JIA, Tian-peng JIANG, and Quan ZHANG declare that they have no conflict of interest.
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Project supported by the National Natural Science Foundation of China (Nos. 61433012 and 61602156), the Project of Science and Technology in Henan Province, China (No. 142102210435), the Project of the Basic and Frontier Technology in Henan Province, China (No. 142300410147), and the PhD Foundation of Henan Polytechnic University, China (No. B2012-099)
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Zhang, Xh., Qian, K., Ren, Jj. et al. Measurement and analysis of content diffusion characteristics in opportunity environmentswith Spark. Frontiers Inf Technol Electronic Eng 20, 1404–1414 (2019). https://doi.org/10.1631/FITEE.1900137
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DOI: https://doi.org/10.1631/FITEE.1900137