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Link state prediction-based reliable transmission for high-speed railway networks

Zhang, Hongke, Quan, Wei, Song, Jiayang, Jiang, Zhongbai and Yu, Shui 2016, Link state prediction-based reliable transmission for high-speed railway networks, IEEE Transactions on Vehicular Technology, vol. 65, no. 12, pp. 9617-9629, doi: 10.1109/TVT.2016.2598473.

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Title Link state prediction-based reliable transmission for high-speed railway networks
Author(s) Zhang, Hongke
Quan, Wei
Song, Jiayang
Jiang, Zhongbai
Yu, ShuiORCID iD for Yu, Shui orcid.org/0000-0003-4485-6743
Journal name IEEE Transactions on Vehicular Technology
Volume number 65
Issue number 12
Start page 9617
End page 9629
Total pages 13
Publisher IEEE
Place of publication Piscataway, N.J.
Publication date 2016-12
ISSN 0018-9545
1939-9359
Keyword(s) Science & Technology
Technology
Engineering, Electrical & Electronic
Telecommunications
Transportation Science & Technology
Engineering
Transportation
High-speed railway (HSR) networks
link state prediction (LSP)
Markov chain
reliable transmission
two-timescale (TTS)
Summary Due to unpredictable noise and ambient interference
along high-speed railways (HSRs), it is challenging to provide reliable
Internet services in severe HSR network environments. Most
existing research that requires expensive modifications for largescale
already in-used base stations cannot be immediately deployed
into the existing HSR systems. In this paper, we propose a quite
lightweight but effective solution to improve the Internet experience
forHSR passengers.Different fromother existing approaches,
we employ a data-driven link state prediction (LSP) mechanism
for HSR reliable transmission, called LSP4HSR, which directly
operates in HSR’s on-board routers. In particular, we conduct an
extensive measurement of network status on several realistic HSR
lines and collect a first-hand dataset in terms of round-trip time
and packet loss rate. By analyzing this real dataset, we find that
HSR link quality presents obvious two-time-scale variation characteristics.
We execute a lot of in-depth studies to explore potential
reasons for this interesting phenomenon. Furthermore, based on
the two-time-scale Markov chain, we establish an accurate HSR
link prediction approach, which brings an LSP-based transmission
enhancement mechanism to alleviate the impact from poor
link status along HSR lines. Extensive experiments verify that the
proposed solution can not only improve the packet transmission
reliability in HSR networks but can be also deployed in existing
HSR systems quite smoothly and easily.
Language eng
DOI 10.1109/TVT.2016.2598473
Field of Research 080503 Networking and Communications
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category C1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2016, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30091355

Document type: Journal Article
Collection: School of Information Technology
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