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• W3113113034 startingPage "1976" @default.
• W3113113034 abstract "Using vehicles as a data mule in vehicular networks contributes to a greater capacity for data offloading from network devices in urban computing scenarios. The biggest obstacle in this type of solution resides in the complexity of managing a communication infrastructure composed of elements spread over different levels of the network. This work proposes the intelligent Edge-Traffic Routing (iETR) architecture, which provides geocast data mule services in urban computing to transport high volumes of data, based on requirements defined by the application. We implement and evaluated iETR through simulation. The results show that it can successfully reduce data transfer times and ensure application scalability, through vehicles distributed at the network edge." @default.
• W3113113034 created "2020-12-21" @default.
• W3113113034 creator A5001176438 @default.
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• W3113113034 date "2021-11-01" @default.
• W3113113034 modified "2023-10-14" @default.
• W3113113034 title "An Intelligent Edge-Traffic Routing Architecture for Vehicular Data-Mule Services" @default.
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• W3113113034 doi "https://doi.org/10.1109/tla.2021.9475852" @default.
• W3113113034 hasPublicationYear "2021" @default.
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