期刊
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
卷 95, 期 -, 页码 212-220出版社
ELSEVIER
DOI: 10.1016/j.future.2018.12.054
关键词
Deep learning; BGP route decision process; Data-driven modeling; Future Internet
资金
- National Natural Science Foundation of China [61572153, 61702220, 61702223]
- National Key research and Development Plan [2018YFB0803504]
Simulating the BGP routing system of Internet is crucial to the analysis of Internet backbone network routing behavior, locating network failure and, evaluating network performance for future Internet. However, the existing BGP routing model lacks in the coarse modeling granularity and the priori knowledge based model. The analysis of BGP routing data that reflects the routing behaviors, directly impacts the BGP routing decision and forward strategy. The efficiency of such analysis dictates the time it takes to come up with such a time-critical decision and strategy. Under the existing model, BGP routing data analysis does not scale up. In this paper, we analyze the inter-domain routing decision making process, then present a prefix level route decision prediction model. More specifically, we apply deep learning methods to build a high-precision BGP route decision process model. Our model handles as much available routing data as possible to promote the prediction accuracy. It analyzes the routing behaviors without any prior knowledge. Beyond discussing the characteristics of the model, we also evaluate the proposed model using experiments explained in detailed cases. For the research community, our method could help in detecting routing dynamics and route anomalies for routing behavior analysis. (C) 2019 Elsevier B.V. All rights reserved.
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