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Pimpisa Watthanavarangkul, "Optimally Placing Multi-Resolution Sensor Logs and Brokers in a Cloud-Fog Topology," Master's Thesis, School of Electrical Engineering and Computer Science, TU Berlin (TUB), March 2021. (Advisor: Daniel Happ; Referees: Falko Dressler and Thomas Sikora)


The Internet of Things (IoT) represents a new range of applications that can benefit from cloud infrastructure. The systems are expected to produce a vast volume of data that needs to be transmitted and preserved. However, there are also disadvantages of the existing approach to connecting edge devices to the cloud, and it is still uncertain to meet the increasing speed of the IoT or the different requirements of IoT applications. Fog computing and publish/subscribe messaging patterns have been introduced to cope with the geo-distributed data on a large scale. Fixed-sized round-robin databases are additionally introduced to limit the growing size of servers and data centers. Storing data is usually achieved with append-only logs. However, the placement of these append-only logs and their brokers in the pub/sub network is still unclear. In this thesis, our goal is to optimally place the log storage and the pub/sub brokers in the given network topology, taking into account diverse network topology factors and network constraints such as the locations of data producers and their application consumers. First, we developed logs and brokers’ placement problems together over the edge, fog, and the cloud nodes as a cost minimization problem utilizing a mathematical programming procedure. Secondly, we developed a meta- heuristics approach in genetic algorithm. Our results strengthen the argument in the discussion that the cloud is usually a good placement option for IoT use cases yet also reveals the benefits of the optimal solution in scenarios with higher clustering levels of the data producers (publishers) and their consumers (subscribers).

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Pimpisa Watthanavarangkul

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    author = {Watthanavarangkul, Pimpisa},
    title = {{Optimally Placing Multi-Resolution Sensor Logs and Brokers in a Cloud-Fog Topology}},
    advisor = {Happ, Daniel},
    institution = {School of Electrical Engineering and Computer Science},
    location = {Berlin, Germany},
    month = {3},
    referee = {Dressler, Falko and Sikora, Thomas},
    school = {TU Berlin (TUB)},
    type = {Master's Thesis},
    year = {2021},

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