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Tasaprom Suptongchai, "Data Management Strategies for Vehicular Micro Clouds using DSRC and D2D Hybrid Networks," Master's Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), July 2021. (Advisor: Gurjashan Singh Pannu; Referees: Falko Dressler and Thomas Sikora)


Recently the vehicular micro cloud architecture has been presented to establish the new generation of Information and Communication Technology (ICT) by enabling cars to provide cloud-like networking and computing services among them. This enables real-time communication, decreases network latency, and further supports future Intelligent Transportation System (ITS) and Internet of Things (IoT) applications. These potential applications have complex requirements, particularly related to data availability and booming data demands. The latter further conducts the problems of overloaded network channels. To address the challenges of data management in vehicular micro clouds, this thesis introduces the data management strategies using DSRC and D2D hybrid networks to cope with data loss issues and keep channel utilization under control. The thesis work composes of two approaches considering in terms of cost efficiency and performance efficiency. The performance of the proposed hybrid-network approaches is evaluated on the Manhattan Grid scenario with different car densities and data sizes against single-network configurations. The results show the increasing data availability up to 30% and the twice number of content replicas as the benefits gained from using hybrid networks compared to the single DSRC channel.

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Tasaprom Suptongchai

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    author = {Suptongchai, Tasaprom},
    title = {{Data Management Strategies for Vehicular Micro Clouds using DSRC and D2D Hybrid Networks}},
    advisor = {Pannu, Gurjashan Singh},
    institution = {School of Electrical Engineering and Computer Science (EECS)},
    location = {Berlin, Germany},
    month = {7},
    referee = {Dressler, Falko and Sikora, Thomas},
    school = {TU Berlin (TUB)},
    type = {Master's Thesis},
    year = {2021},

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