Optimization Configuration Model for Intelligent Measurement Multi-Core Modules Considering “Cloud-Edge-End-Core” Collaboration
The new power system with new energy as the main body gives the low-voltage distribution network (LVDN) a richer connotation, requiring intelligent measurement equipment to have good scalability and collaborative ability. To address these requirements, an optimization configuration model for intelli...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10844280/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832576749916913664 |
|---|---|
| author | Lai Zhou Qinhao Li Guoying Lin |
| author_facet | Lai Zhou Qinhao Li Guoying Lin |
| author_sort | Lai Zhou |
| collection | DOAJ |
| description | The new power system with new energy as the main body gives the low-voltage distribution network (LVDN) a richer connotation, requiring intelligent measurement equipment to have good scalability and collaborative ability. To address these requirements, an optimization configuration model for intelligent measurement multi-core modules considering “cloud-edge-end-core” collaboration is proposed in this paper. Initially, a technical framework for “cloud-edge-end-core” collaboration in intelligent measurement is designed, expanding the conventional “cloud-edge-end” vertical cooperation architecture with multi-core module collaboration and horizontal synergy at the same hierarchical level to enhance the flexibility of data interaction. Then, an optimization configuration model for multi-core modules is formulated, to minimize both the chip configuration costs and the data transmission costs associated with “cloud-edge-end-core” collaboration. The decision variables include the core chip level of the intelligent measurement terminal, the management core chip level for smart meters, and the placement of application configurations. Finally, the effectiveness of the proposed model is verified in the LVDN with 300 users. The performance of the proposed optimization configuration model in different scenarios is compared and the influence of model parameters on the optimization results is analyzed. The results show that the proposed multi-core module optimization configuration model can optimize the selection of intelligent measurement terminal core and smart meter management core according to different application data requirements. It meets the application requirements while minimizing the multi-core module optimization configuration cost and the “cloud-edge-end-core” collaboration cost. |
| format | Article |
| id | doaj-art-3e2e9f841fb34900ab45f88500bde170 |
| institution | Kabale University |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-3e2e9f841fb34900ab45f88500bde1702025-01-31T00:01:31ZengIEEEIEEE Access2169-35362025-01-0113182281823810.1109/ACCESS.2025.353095310844280Optimization Configuration Model for Intelligent Measurement Multi-Core Modules Considering “Cloud-Edge-End-Core” CollaborationLai Zhou0https://orcid.org/0000-0002-4313-9462Qinhao Li1Guoying Lin2Intelligent Vehicle College, Guangzhou Panyu Polytechnic, Guangzhou, ChinaIntelligent Vehicle College, Guangzhou Panyu Polytechnic, Guangzhou, ChinaGuangdong Provincial Key Laboratory of New Technology for Smart Grid, China Southern Power Grid Technology Company Ltd., Guangzhou, ChinaThe new power system with new energy as the main body gives the low-voltage distribution network (LVDN) a richer connotation, requiring intelligent measurement equipment to have good scalability and collaborative ability. To address these requirements, an optimization configuration model for intelligent measurement multi-core modules considering “cloud-edge-end-core” collaboration is proposed in this paper. Initially, a technical framework for “cloud-edge-end-core” collaboration in intelligent measurement is designed, expanding the conventional “cloud-edge-end” vertical cooperation architecture with multi-core module collaboration and horizontal synergy at the same hierarchical level to enhance the flexibility of data interaction. Then, an optimization configuration model for multi-core modules is formulated, to minimize both the chip configuration costs and the data transmission costs associated with “cloud-edge-end-core” collaboration. The decision variables include the core chip level of the intelligent measurement terminal, the management core chip level for smart meters, and the placement of application configurations. Finally, the effectiveness of the proposed model is verified in the LVDN with 300 users. The performance of the proposed optimization configuration model in different scenarios is compared and the influence of model parameters on the optimization results is analyzed. The results show that the proposed multi-core module optimization configuration model can optimize the selection of intelligent measurement terminal core and smart meter management core according to different application data requirements. It meets the application requirements while minimizing the multi-core module optimization configuration cost and the “cloud-edge-end-core” collaboration cost.https://ieeexplore.ieee.org/document/10844280/Low-voltage distribution network“cloud-edge-end-core” collaborationintelligent measurement equipmentmulti-core modulesoptimization configuration model |
| spellingShingle | Lai Zhou Qinhao Li Guoying Lin Optimization Configuration Model for Intelligent Measurement Multi-Core Modules Considering “Cloud-Edge-End-Core” Collaboration IEEE Access Low-voltage distribution network “cloud-edge-end-core” collaboration intelligent measurement equipment multi-core modules optimization configuration model |
| title | Optimization Configuration Model for Intelligent Measurement Multi-Core Modules Considering “Cloud-Edge-End-Core” Collaboration |
| title_full | Optimization Configuration Model for Intelligent Measurement Multi-Core Modules Considering “Cloud-Edge-End-Core” Collaboration |
| title_fullStr | Optimization Configuration Model for Intelligent Measurement Multi-Core Modules Considering “Cloud-Edge-End-Core” Collaboration |
| title_full_unstemmed | Optimization Configuration Model for Intelligent Measurement Multi-Core Modules Considering “Cloud-Edge-End-Core” Collaboration |
| title_short | Optimization Configuration Model for Intelligent Measurement Multi-Core Modules Considering “Cloud-Edge-End-Core” Collaboration |
| title_sort | optimization configuration model for intelligent measurement multi core modules considering x201c cloud edge end core x201d collaboration |
| topic | Low-voltage distribution network “cloud-edge-end-core” collaboration intelligent measurement equipment multi-core modules optimization configuration model |
| url | https://ieeexplore.ieee.org/document/10844280/ |
| work_keys_str_mv | AT laizhou optimizationconfigurationmodelforintelligentmeasurementmulticoremodulesconsideringx201ccloudedgeendcorex201dcollaboration AT qinhaoli optimizationconfigurationmodelforintelligentmeasurementmulticoremodulesconsideringx201ccloudedgeendcorex201dcollaboration AT guoyinglin optimizationconfigurationmodelforintelligentmeasurementmulticoremodulesconsideringx201ccloudedgeendcorex201dcollaboration |