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- W3089605287 abstract "Abstract In big cities, with heavy traffic, tracking vehicle movements undoubtedly generates big data, which can be cumbersome for real time analysis. In the other hand, the process of roadside unit (RSUs) deployment in Vehicular Ad-hoc Networks (VANETs) mainly relies on the analysis of vehicles trajectories, which is considered as big sequential data. The complexity comes from (i) the number of transactions recorded at each time and (ii) the redundancy of transactions in the database. In this respect, several research works focusing on RSUs deployment have been proposed. The thriving challenge would be to (i) reduce the deployment cost by minimizing as far as possible the number of used RSUs; and (ii) to maximize the coverage ratio. In this paper, we introduce a spatio-temporal RSU deployment method consisting of two main parts namely ”finding representative transactions from the sequential database” and ”computing coverage”. The first one identifies the representative transactions, a.k.a transactions having a high utility, from a large sequential database. The second part computes a minimal set of junctions, where RSUs have to be ideally placed. The performed experiments show that our scheme outperforms its competitors in terms of cost, time performance as well as coverage ratio." @default.
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- W3089605287 date "2020-01-01" @default.
- W3089605287 modified "2023-10-17" @default.
- W3089605287 title "An efficient roadside unit deployment method for vehicular ad-hoc networks" @default.
- W3089605287 doi "https://doi.org/10.1016/j.procs.2020.09.072" @default.
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