Fog Computing for Big Data Analytics in IoT Aided Smart Grid Networks
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Fog Computing for Big Data Analytics in IoT Aided Smart Grid Networks Md. Muzakkir Hussain1 · M. M. Sufyan Beg1 · Mohammad Saad Alam2
© Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract The recent integration of Internet of Things and Cloud Computing (CC) technologies into a Smart Grid (SG) revolutionizes its operation. The scalable and unlimited Store Compute and Networking (SCN) resources offered by CC enables efficient Big Data Analytics of SG data. However, due to remote location of Cloud Data Centers and congested network traffic, the cloud often gives poor performance for latency and energy critical SG applications. Fog Computing (FC) is thus proposed as a model that distributes the SCN resources at the intermediary devices, termed as Fog Computing Nodes (FCN), viz. network gateways, battery powered servers, access points, etc. By executing application specific logic at those nodes, the FC astonishingly reduces the response time as well as energy consumption of network elements. In this paper, we propose a mathematical framework that explains the Planning and Placement of Fog computing in smart Grid (PPFG). Basically, the PPFG model is formulated as an Integer Linear Programming problem that determines the optimal location, the capacity and the number of FCNs, towards minimizing the average response delay and energy consumption of network elements. Since this optimization problem is trivially NP-Hard, we solve it using an evolutionary Non-dominated Sorting Genetic Algorithm. By running the model on an exemplary SG network, we demonstrate the operation of proposed PPFG model. In fact, we perform a complete analysis of the obtained Pareto Fronts (PF), in order to better understand the working of design constraints in the PPFG model. The PFs will enable the SG utilities and architectural designers to evaluate the pros and cons of each of the trade-off solutions, leading to intelligent planning, designing and deployment of FC based SG applications. Keywords Big data analytics · Cloud computing · Fog computing · Smart grid * Md. Muzakkir Hussain [email protected] M. M. Sufyan Beg [email protected] Mohammad Saad Alam [email protected] 1
Department of Computer Engineering, Zakir Husain College of Engineering & Technology, Aligarh, India
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Department of Electrical Engineering, Zakir Husain College of Engineering & Technology, Aligarh, India
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Abbreviations CC Cloud computing EV Electric vehicles FC Fog computing SG Smart grid BDA Big data analytics CDC Cloud data centers CPS Cyber-physical system FCN Fog computing node HMI Human machine interface ICT Information and communication technologies M2M Machine-to-machine NSGA-II Non-dominated sorting genetic algorithm SCADA Supervisor control and data acquisition SG-CPS Smart grid cyber-physical system
1 Introduction The Smart Grid (SG) is a modernized power grid enabled with state-of-the-art ICT facilities [1]. It improves the reliability, efficien
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