Edge-Node-Aware Adaptive Data Processing Framework for Smart Grid
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Smart grid is an autonomous power generation and production system, that includes various energy management sub-systems such as energy efficient resources, smart appliances, renewable energy resources and smart meters. It is a sensory-based power network that adopts digital technology to supply electricity to consumers and industries. Recently, it is observed that the grid infrastructure is rapidly transforming network topology towards green and eco-friendly computing. For this, edge-computing environment is being adopted to inter-connect distributed IoT nodes in peer-to-peer sequential order. With this approach, the grid ideally cope to green computing issues than traditional infrastructure, however, it faces certain data processing problems such as differentiating IoT and non-IoT data segments, storing data chunk with end of file (EOF) assurance, management of replica data segments and systematic analytics of edge node datasets. This produces operational latency at edges as well as onto segment reservoir and results delay in exchanging data segments at smart grid. This paper presents an Edge-node-aware framework that empowers nodes to intelligently process IoT and counterpart data segments, a portable plugin to identify EOF data chunk, reliable replica management system and hassle-free dataset analytics. The simulation results show that the proposed framework effectively manage data segments and store into smart grid reservoir.
KeywordsSmart grid Smart meters Edge computing Data block processing Replica management
- 4.Hussain, Md., Alam, M. S., & Beg, M. M. (2018). Fog computing in IoT aided smart grid transition-requirements, prospects, status quos and challenges. arXiv preprint arXiv:1802.01818.
- 5.Bonomi, F., et al. (2012). Fog computing and its role in the internet of things. In Proceedings of the first edition of the MCC workshop on mobile cloud computing. ACM.Google Scholar
- 7.Ashok, K., Divan, D., & Lambert, F. (2018). Grid edge analytics platform with AMI data. In 2018 IEEE power & energy society innovative smart grid technologies conference (ISGT). IEEE.Google Scholar
- 8.Simmhan, Y., et al. (2018). Towards a datadriven IoT software architecture for smart city utilities. Software: Practice and Experience, 48(7), 1390–1416.Google Scholar
- 17.Qureshi, N. M. F., et al. (2018). An aggregate mapreduce data block placement strategy for wireless IoT edge nodes in smart grid. Wireless Personal Communications, 1–12.Google Scholar
- 18.Power Grid Datasets. https://github.com/ComplexNetTSP/ComplexNetWiki/wiki/PowerGrid-datasets. Accessed Sept 2018.