Feasibility of Fog Computing in Smart Grid Architectures

Contemporary Smart Grid (SG) systems are enticed by smart devices and entities due to unfolded developments in both the IT sectors viz. Intelligent Transportation and Information Technology. The intelligent transportation infrastructure elements when bestowed with Internet of Things (IoT) and sensor network of latter IT (Information Technology), makes every object active and brings them online. In such scenario, the traditional cloud deployment perishes to meet the analytics and computational exigencies for such dynamic cum resource-time critical subsystems. Starting with highlighting the mission-critical requirements of an idealized SG infrastructure, this work proposes an edge-centered FOG (From cOre to edGe) computing model primarily focused to realize the processing and computational objectives of SG. The objective of this work is to comprehend the applicability of FOG computing algorithms to interplay with the core-centered cloud computing support, thus enabling to come up with a new breed of real-time and latency free utilities. Further, for demonstrating the feasibility of the proposed framework, the SG use case is considered and an exemplary FOG Service-Oriented Architecture (SOA) is depicted. Finally, the potential adoption challenges elucidated in the realization of the proposed framework are highlighted along with nascent research domains that call for efforts and investments in successfully guiding the FOG approaches into a pinnacle.

[1]  Xi Fang,et al.  3. Full Four-channel 6.3-gb/s 60-ghz Cmos Transceiver with Low-power Analog and Digital Baseband Circuitry 7. Smart Grid — the New and Improved Power Grid: a Survey , 2022 .

[2]  Rajkumar Buyya,et al.  Fog Computing: Principles, Architectures, and Applications , 2016, ArXiv.

[3]  Mohsen Guizani,et al.  Internet of Things: A Survey on Enabling Technologies, Protocols, and Applications , 2015, IEEE Communications Surveys & Tutorials.

[4]  Zhifeng Xiao,et al.  Security and Privacy in Cloud Computing , 2013, IEEE Communications Surveys & Tutorials.

[5]  Ciprian Dobre,et al.  Big Data and Internet of Things: A Roadmap for Smart Environments , 2014, Big Data and Internet of Things.

[6]  Sateesh Addepalli,et al.  Fog computing and its role in the internet of things , 2012, MCC '12.

[7]  Sudip Misra,et al.  Assessment of the Suitability of Fog Computing in the Context of Internet of Things , 2018, IEEE Transactions on Cloud Computing.

[8]  Donghyun Kim,et al.  On security and privacy issues of fog computing supported Internet of Things environment , 2015, 2015 6th International Conference on the Network of the Future (NOF).

[9]  Tetsutaro Uehara,et al.  Fog Computing: Issues and Challenges in Security and Forensics , 2015, 2015 IEEE 39th Annual Computer Software and Applications Conference.

[10]  Ahmad Almadhor,et al.  A Fog Computing based Smart Grid Cloud Data Security , 2016 .

[11]  Depeng Jin,et al.  Vehicular Fog Computing: A Viewpoint of Vehicles as the Infrastructures , 2016, IEEE Transactions on Vehicular Technology.

[12]  Rajkumar Buyya,et al.  Feasibility of Fog Computing , 2017, Scalable Computing and Communications.

[13]  Suat Özdemir,et al.  A fog computing based smart grid model , 2016, 2016 International Symposium on Networks, Computers and Communications (ISNCC).

[14]  Ivan Stojmenovic,et al.  The Fog computing paradigm: Scenarios and security issues , 2014, 2014 Federated Conference on Computer Science and Information Systems.