IEEE Network · 2019 · 39 citations · 11 references
ComputingComputer ScienceComputer SystemsComputer NetworksEdge ComputingMobile ComputingEdge ArchitectureEdge NetworkingMobile Edge ComputingMulti-access Edge ComputingVehicle-to-everything CommunicationAggregationContext-aware CommunicationData CachingEdge Computing For Vehicular NetworksMobile Edge Computing ArchitectureRoute AggregationUnlicensed SpectrumVehicular Edge Computing
Efficient use of diverse wireless spectrums is essential to meet application demands in Internet of Vehicles, given the dynamic network environment. The study proposes a context‑aware communication approach that integrates licensed and unlicensed spectrums using edge computing. The approach combines joint aggregation, caching, and decentralization, introduces asynchronous multihop broadcast and unicast schemes, and is evaluated via computer simulations against baseline methods.
In order to satisfy the application requirements in Internet of Vehicles scenarios, it is important to efficiently utilize different wireless spectrums while considering the dynamic features of network environments. In this article, we propose a context-aware communication approach to efficiently integrate different licensed and unlicensed spectrums leveraging the edge computing technologies. In addition, a joint aggregation, caching, and decentralization scheme is proposed to efficiently combine route aggregation, data caching, and decentralized computing approaches to compensate for the limited wireless resources. Asynchronous multihop broadcast and asynchronous multihop unicast schemes are introduced to improve the routing performance in multihop broadcast and multihop unicast communications, respectively. We conduct computer simulations to evaluate the effects of the proposed scheme by comparing it with other baseline approaches.
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5G mmWave Positioning for Vehicular Networks
Henk Wymeersch, Gonzalo Seco‐Granados, Giuseppe Destino et al. · IEEE Wireless Communications · 2017 · 456 citations · Full text
BEGIN: Big Data Enabled Energy-Efficient Vehicular Edge Computing
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