Xiaoyun Yan
Beijing Jiaotong University
10 Papers
27 Citations
Xiaoyun Yan is an academic researcher from Beijing Jiaotong University. The author has contributed to research in topics: Vehicular ad hoc network & Wireless network. The author has an hindex of 4, co-authored 10 publications.
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Papers
Enhancing Vehicular Communication Using 5G-Enabled Smart Collaborative Networking
TL;DR: The real-world experimental results demonstrate that SCVN achieves better performance in throughput, reliability, and handover latency compared to its counterparts, and the proposed architecture can take a solid step toward increasing bandwidth and improving reliability for vehicular communications.
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Fuzzy and Utility Based Network Selection for Heterogeneous Networks in High-Speed Railway
TL;DR: The proposed FSNS is a novel dynamic imprecise-aware network selection approach that outperforms both TOPSIS and FMADM for a good performance improvement and a preferable decision to keep relative stability and reduce abnormal selections.
Congestion Game With Link Failures for Network Selection in High-Speed Vehicular Networks
TL;DR: The results demonstrate that E-CGF outperforms others by alleviating network congestion and improving transmission reliability with a moderate trade-off between achieved throughput and transit cost.
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Improving bandwidth utilization by compressing small-payload traffic for vehicular networks:
TL;DR: A scalable end-to-end header compression scheme is proposed, which takes advantage of the locator/identifier separation concept and some characteristics of software-defined networking, and uses a forwarding identifier to indicate the compressor’s location, separating the header compression process from the packet forwarding process.
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Fuzzy Multi-Attribute Utility Based Network Selection Approach for High-Speed Railway Scenario
Xiaoyun Yan,Ping Dong,Tao Zheng,Hongke Zhang,Shui Yu +4 more
- 01 Dec 2017
TL;DR: This paper designs a novel dynamic imprecise-aware network selection approach, named FSNS by taking advantage of fuzzy logic and utility function of multiple attributes and demonstrates that FSNS outperforms TOPSIS for a preferable decision to keep relatively stable and reduce abnormal selection.
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