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A balanced cooperative downloading method for VANET

Authors: Jianhang Liu; Haibin Zhai; Zhixuan Jia; Shibao Li; Haihua Chen 0003; Xue-rong Cui;

A balanced cooperative downloading method for VANET

Abstract

Cooperative downloading is going to improve the amount of downloaded data to the users of Vehicular Networking (VANET). Pointing at the problems of the low utilization of the spatiotemporal resource in DA and unbalance service of cooperative downloading, this paper proposed a balanced cooperative downloading method, which makes use of Euclidean Distance and Manhattan Distance dynamically as one of the principle to selecting the vehicles according to the number of the clients, aiming to keep balanced downloading. On the premise of ensuing throughput, the system can provide relative balanced service using this method. Simulation results indicate the benefits of the proposed scheme in terms of increasing efficiency and balanced profit.

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Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
Average
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