Abstract
Computing shortest paths between a pair of nodes on a rapidly evolving network is a fundamental operation, and it is applied to wide range of networks. Classical exact methods for this problem can not extend to large-scale dynamic graphs. Meanwhile, existing approximate landmark-based methods can not be simply adapted for dynamic weighted graphs. In this paper, we consider four modifications on networks, including multi-edge insertions and deletions, weight increments and decrements. To address problems above, we present two improvements to existing methods: a novel method of indexing a weighted graph and high efficiency of approximating arbitrary pairs of nodes. Experimental results demonstrate that much faster and more precise estimation is achieved by our approaches.
This work was supported by National Basic Research Program of China (973 Program) (No. 2012CB316205), NSFC under the grant No.61272137, 61033010, 61202114, and NSSFC (No: 12 & ZD220). It was partially done when the authors worked in SA Center for Big Data Research in RUC. This Center is funded by a Chinese National “111” Project “Attracting International in Data Engineering Research”.
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Jin, J., Shi, X., Li, C., Chen, H. (2014). Fast Approximation of Shortest Path on Dynamic Information Networks. In: Li, F., Li, G., Hwang, Sw., Yao, B., Zhang, Z. (eds) Web-Age Information Management. WAIM 2014. Lecture Notes in Computer Science, vol 8485. Springer, Cham. https://doi.org/10.1007/978-3-319-08010-9_30
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DOI: https://doi.org/10.1007/978-3-319-08010-9_30
Publisher Name: Springer, Cham
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