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Title A Zero Emission Neighbourhoods Data Management Architecture for Smart City Scenarios: Discussions toward 6Vs challenges
ID_Doc 37467
Authors Sinaeepourfard, A; Krogstie, J; Petersen, SA; Gustaysen, A
Title A Zero Emission Neighbourhoods Data Management Architecture for Smart City Scenarios: Discussions toward 6Vs challenges
Year 2018
Published
Abstract A huge volume of data are being generated from multiple sources, including smart cities, the IoT devices, scientific modeling, or different big data simulations; but also from users' daily activities. These daily new data are added to historical repositories, providing the huge and complex universe of the digital data. Recently, the Fog-to-Cloud (F2C) data management architecture is envisioned to handle all big data complexities, from IoT devices (the closest layer to the users) to cloud technologies (the farthest layer to the IoT devices), as well as different data phases from creation to usage from fog to cloud scenario. Moreover, the F2C data management architecture can have several benefits from the combined advantages of fog (distributed) and cloud (centralized) technologies including reducing network traffic, reducing latencies drastically while improving security. In this paper, we have several novel contributions. First, we described the previous studies of the Zero Emission Buildings (ZEB) in the context of the data flow and movement architecture. Second, we have proposed Zero Emission Neighbourhoods (ZEN) data management architecture for smart city scenarios based on a distributed hierarchical F2C data management. Indeed, we used the 6Vs big data challenges (Volume, Variety, Velocity, Variability, Veracity, and Value) for evaluating the data management architectures (including ZEB and ZEN). The result of the evaluation shows that our proposed ZEN data management architecture can address 6Vs challenges and is able to manage the data lifecycle from its production up to its usage.
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