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Erschienen in: Wireless Personal Communications 1/2019

27.03.2019

Edge-Node-Aware Adaptive Data Processing Framework for Smart Grid

verfasst von: Isma Farah Siddiqui, Nawab Muhammad Faseeh Qureshi, Bhawani Shankar Chowdhry, Muhammad Aslam Uqaili

Erschienen in: Wireless Personal Communications | Ausgabe 1/2019

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Abstract

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.

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Metadaten
Titel
Edge-Node-Aware Adaptive Data Processing Framework for Smart Grid
verfasst von
Isma Farah Siddiqui
Nawab Muhammad Faseeh Qureshi
Bhawani Shankar Chowdhry
Muhammad Aslam Uqaili
Publikationsdatum
27.03.2019
Verlag
Springer US
Erschienen in
Wireless Personal Communications / Ausgabe 1/2019
Print ISSN: 0929-6212
Elektronische ISSN: 1572-834X
DOI
https://doi.org/10.1007/s11277-019-06264-7

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