An Overview of Fog Data Analytics for IoT Applications

Sensors (Basel). 2022 Dec 24;23(1):199. doi: 10.3390/s23010199.

Abstract

With the rapid growth in the data and processing over the cloud, it has become easier to access those data. On the other hand, it poses many technical and security challenges to the users of those provisions. Fog computing makes these technical issues manageable to some extent. Fog computing is one of the promising solutions for handling the big data produced by the IoT, which are often security-critical and time-sensitive. Massive IoT data analytics by a fog computing structure is emerging and requires extensive research for more proficient knowledge and smart decisions. Though an advancement in big data analytics is taking place, it does not consider fog data analytics. However, there are many challenges, including heterogeneity, security, accessibility, resource sharing, network communication overhead, the real-time data processing of complex data, etc. This paper explores various research challenges and their solution using the next-generation fog data analytics and IoT networks. We also performed an experimental analysis based on fog computing and cloud architecture. The result shows that fog computing outperforms the cloud in terms of network utilization and latency. Finally, the paper is concluded with future trends.

Keywords: Internet of things; artificial intelligence; blockchain; data analytics; fog computing.

Publication types

  • Review

Grants and funding

This paper was partially supported by UEFISCDI Romania and MCI through BEIA projects SOLID-B5G, T4ME2, DISAVIT, AISTOR, MULTI-AI, ADRIATIC, Hydro3D, PREVENTION, DAFCC, EREMI, ADCATER, MUSEION, iPREMAS, IPSUS, U-GARDEN, CREATE and by European Union’s Horizon 2020 research and innovation program under grant agreement No. 101037866 (ADMA TranS4MErs) and and No. 101016567 (VITAL-5G). The results were obtained with the support of the Ministry of Investments and European Projects through the Human Capital Sectoral Operational Program 2014-2020, Contract no. 62461/03.06.2022, SMIS code 153735. This work is supported by Ministry of Research, Innovation, Digitization from Romania by the National Plan of R & D, Project PN 19 11, Subprogram 1.1. Institutional performance-Projects to finance excellence in RDI, Contract No. 19PFE/30.12.2021 and a grant of the National Center for Hydrogen and Fuel Cells (CNHPC)—Installations and Special Objectives of National Interest (IOSIN).