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ChainCluster : engineering a cooperative content distribution framework for highway vehicular communications

Zhou, Haibo, Liu, Bo, Luan, Tom H., Hou, Fen, Gui, Lin, Li, Ying, Yu, Quan and Shen, Xuemin (Sherman) 2014, ChainCluster : engineering a cooperative content distribution framework for highway vehicular communications, IEEE transactions on intelligent transportation system, vol. 15, no. 6, pp. 2644-2657.

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Title ChainCluster : engineering a cooperative content distribution framework for highway vehicular communications
Author(s) Zhou, Haibo
Liu, Bo
Luan, Tom H.
Hou, Fen
Gui, Lin
Li, Ying
Yu, Quan
Shen, Xuemin (Sherman)
Journal name IEEE transactions on intelligent transportation system
Volume number 15
Issue number 6
Start page 2644
End page 2657
Total pages 14
Publisher IEEE
Place of publication Piscataway, N. J.
Publication date 2014-12
ISSN 1558-0016
Keyword(s) clustering
cooperative content distribution
drive-thru internet
highways
Summary The recent advances in wireless communication techniques have made it possible for fast-moving vehicles to download data from the roadside communications infrastructure [e.g., IEEE 802.11b Access Point (AP)], namely, Drive-thru Internet. However, due to the high mobility, harsh, and intermittent wireless channels, the data download volume of individual vehicle per drive-thru is quite limited, as observed in real-world tests. This would severely restrict the service quality of upper layer applications, such as file download and video streaming. On addressing this issue, in this paper, we propose ChainCluster, a cooperative Drive-thru Internet scheme. ChainCluster selects appropriate vehicles to form a linear cluster on the highway. The cluster members then cooperatively download the same content file, with each member retrieving one portion of the file, from the roadside infrastructure. With cluster members consecutively driving through the roadside infrastructure, the download of a single vehicle is virtually extended to that of a tandem of vehicles, which accordingly enhances the probability of successful file download significantly. With a delicate linear cluster formation scheme proposed and applied, in this paper, we first develop an analytical framework to evaluate the data volume that can be downloaded using cooperative drive-thru. Using simulations, we then verify the performance of ChainCluster and show that our analysis can match the simulations well. Finally, we show that ChainCluster can outperform the typical studied clustering schemes and provide general guidance for cooperative content distribution in highway vehicular communications.
Language eng
Field of Research 080502 Mobile Technologies
Socio Economic Objective 890103 Mobile Data Networks and Services
HERDC Research category C1 Refereed article in a scholarly journal
Copyright notice ©2014, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30064968

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Created: Tue, 15 Jul 2014, 19:37:05 EST by Tom Luan

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