F2c2C-DM: A Fog-to-cloudlet-to-Cloud Data Management Architecture in Smart City

Abstract

Smart city solutions make a high-level technological innovation in a city to expand their citizens' quality of life by several different technological management strategies (such as resource management and data management) among end-users, city planners, and technological devices (e.g., sensors, IoT devices, etc.). Currently, data management architectures have been offered by some researchers to organize obtained data in smart cities, including Centralized Data Management (CDM) and Distributed-to-Centralized Data Management (D2C-DM). In addition, the D2C-DM architecture can provide several advantages from the combined advantages of distributed (e.g., Fog) and centralized (e.g., Cloud) technologies, such as reducing network traffic and their latencies, upgrading the security levels and so on. In this paper, we propose several novel contributions. First, we design a D2C-DM with Fog, cloudlet, and Cloud technologies to organize huge amounts of the data production in smart city scenarios, from physical devices (including IoT and sensors devices) to non-physical devices (including third-party applications, and other databases). Second, we tailor our proposed D2C-DM architecture with the Zero Emission Neighborhoods (ZEN) scenario to manage its different data types, including context, research, and Key Performance Indicator (KPI) data. Finally, the advantages of this D2C-DM architecture are discussed.

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“…IoT hub is a new component in this architecture and other elements are the same as previous research of [23] and [27]. The final research of the series replaces IoT hub by the cloudlet layer [14], where a hybrid data management architecture combined with smart city scenario and ZEN center scenario are demonstrated. The architecture helps to reduce data traffic and latency of smart city data management.…”

“…Cloud computing is one of the preferable data management technologies for developing smart cities [14]. To decrease the data traffic load and latency, other computing methods can be integrated with Cloud computing [14,17]. Cloud is large storage where a huge amount of data can be stored [14].…”

“…To decrease the data traffic load and latency, other computing methods can be integrated with Cloud computing [14,17]. Cloud is large storage where a huge amount of data can be stored [14]. It is also exploited for machine learning (ML), data analytics, visualization, and other operations [17].…”

“…Every layer will perform a different function and maintain a chain of data flow [25]. Moreover, the layers carry different types of data, such as random data, historical data, KPI data, and research data [14].…”

“…So, it is an alarming policy making issue for the authorities because the cities will have to manage a vast population and thereby the possible smart city concept is no longer a dream. In a smart city, all the smart devices will integrate into a central system [14]. The service providers in the city will get the necessary access of respective information from the system and will act accordingly [15].…”