Abstract
To the delay problem in interweaving coding algorithm and lost data caused by channel fading and congestion, a fault-tolerant transfer algorithm based on principal component analysis (PCA) is proposed in this paper. In the algorithm, PCA is used to decompose track data and the largest principal component is found. Then, only selected special data needs to be retransferred, which can reduce the acknowledging time in short-time link in opportunistic networks. Receiving nodes can recover lost data based on principal component. The algorithm can be used to monitor moving track of wild animals. Theoretical analysis shows that the algorithm can improve the transferring efficiency.
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Cheng, F., Zhang, J. (2011). Fault-Tolerant Transfer Algorithm Based on Principal Component Analysis in Opportunistic Networks. In: Lin, S., Huang, X. (eds) Advances in Computer Science, Environment, Ecoinformatics, and Education. CSEE 2011. Communications in Computer and Information Science, vol 216. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23345-6_94
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DOI: https://doi.org/10.1007/978-3-642-23345-6_94
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-23344-9
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