Link State Prediction-Based Reliable Transmission for High-Speed Railway Networks

Zhang, H; Quan, W; Song, J; Jiang, Z; Yu, S

Link State Prediction-Based Reliable Transmission for High-Speed Railway Networks

Zhang, H Quan, W Song, J Jiang, Z Yu, S

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Publisher:: IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Publication Type:: Journal Article
Citation:: IEEE Transactions on Vehicular Technology, 2016, 65, (12), pp. 9617-9629
Issue Date:: 2016-12-01

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Field	Value	Language
dc.contributor.author	Zhang, H
dc.contributor.author	Quan, W
dc.contributor.author	Song, J
dc.contributor.author	Jiang, Z
dc.contributor.author	Yu, S https://orcid.org/0000-0003-4485-6743
dc.date.accessioned	2022-07-31T01:03:10Z
dc.date.available	2022-07-31T01:03:10Z
dc.date.issued	2016-12-01
dc.identifier.citation	IEEE Transactions on Vehicular Technology, 2016, 65, (12), pp. 9617-9629
dc.identifier.issn	0018-9545
dc.identifier.issn	1939-9359
dc.identifier.uri	http://hdl.handle.net/10453/159405
dc.description.abstract	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 large-scale 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 for HSR passengers. Different from other 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.
dc.language	English
dc.publisher	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
dc.relation.ispartof	IEEE Transactions on Vehicular Technology
dc.relation.isbasedon	10.1109/TVT.2016.2598473
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	08 Information and Computing Sciences, 09 Engineering, 10 Technology
dc.subject.classification	Automobile Design & Engineering
dc.title	Link State Prediction-Based Reliable Transmission for High-Speed Railway Networks
dc.type	Journal Article
utslib.citation.volume	65
utslib.for	08 Information and Computing Sciences
utslib.for	09 Engineering
utslib.for	10 Technology
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
utslib.copyright.status	closed_access	*
dc.date.updated	2022-07-31T01:03:08Z
pubs.issue	12
pubs.publication-status	Published
pubs.volume	65
utslib.citation.issue	12

Abstract:

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 large-scale 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 for HSR passengers. Different from other 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.

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http://hdl.handle.net/10453/159405