Industry 4.0 CAMI: An Elastic Cloud Zynq UltraScale FPGA Metering Architecture

Abstract

In the era of Industry 4.0, commoditized services (such as electricity, healthcare, etc.), require accuracy, availability, security and Quality of service (QoS) in the Cloud space. This paper presents cloud advanced metering infrastructure (CAMI) using Zynq UltraScale+ device field programmable gate array (FPGA). The architectural layout for energy tracking and profile measurement is discussed. Unlike existing systems with digital signal processors, it uses precision-based meter reading with encryption driven demand side management (DSM) to protect end-users. An energy service application with supporting hardware prototype is designed. Cryptographic algorithms, dynamic auto-scaling and predictive QoS provisioning are introduced as features of its backend cloud virtualization Infrastructure controller (CVIC). Process integration is achieved with CVIC synthesis for energy analytics and DSM. For the use case scenario, the CAMI prototype runs on Zynq UltraScale+ device with support for end-to-end dataset captures. The system provides on-demand visualization of energy consumption patterns for the end-users. In the experimental setup, two case scenarios demonstrate how the metering system executes fast edge computing profiling. Optimal performance is achieved for latency, utilization, and throughput under CVIC overhead constraint. It was observed that resource utilization responses for heterogeneous and non heterogeneous CVIC are 71.43% and 28.57% respectively. Latency profiles gave 71.43% and 28.57% respectively. With the VM controller, FPGA CAMI offered 47.36% while without VM controller, 52.63% throughput is observed. Consequently, the results highlights how FPGA hardware acceleration can significantly improve request distribution as well as workload processing for cloud based metering systems.

Design of industrial equipment data acquisition system based on ZYNQ

“…After simulation experiments, the research results show that real-time unmanned monitoring is achieved, providing a reference for the future operation and maintenance of power grid equipment. Literature [18] uses Cloud Advanced Metering Infrastructure (CAMI) with Zynq UltraScale+ device Field Programmable Gate Array (FPGA), comparing with existing Digital Signal Processing (DSM) systems, which uses DSM driven by accurate transcription and encryption to serve end-users. Literature [19] describes the data collection for a high particle-strength analog thermon calorimeter at the future International Linear Collider, focusing on the central ZYNQ-Sysem-On-Chip to demonstrate in detail the high performance and stability of this data collection system.…”