<![CDATA[The vision of sustainable development goal 9 (SDG 9) is realized through the integration of innovative technologies in the cyber-physical system (CPS). This work focuses on a smart network meter (SNM) application, designed to manage the extensive big data analytics required for processing and analyzing vast amounts of aggregated data in a short period. To address these demands, an advanced explicitly parallel instruction computing (AEPIC) approach is employed, leveraging a multi-core hardware security module (HSM) built on the elliptic curve cryptography (ECC) algorithm. Implementing the algorithm on various field programmable gate arrays (FPGAs) ensures adaptability to different hardware configurations, delivering scalable and optimized performance for big data aggregation in SNM applications. The proposed module showcases exceptional performance in design analysis. The Virtex-7 FPGA demonstrates excellent suitability for big data analytics in smart network applications, with dynamic power consumption accounting for 55% of total power and an on-chip power of 0.542 watts.]]>
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