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Multi-source heterogeneous data access management framework and key technologies for electric power Internet of Things
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作者 Pengtian Guo Kai Xiao +1 位作者 Xiaohui Wang Daoxing Li 《Global Energy Interconnection》 EI CSCD 2024年第1期94-105,共12页
The power Internet of Things(IoT)is a significant trend in technology and a requirement for national strategic development.With the deepening digital transformation of the power grid,China’s power system has initiall... The power Internet of Things(IoT)is a significant trend in technology and a requirement for national strategic development.With the deepening digital transformation of the power grid,China’s power system has initially built a power IoT architecture comprising a perception,network,and platform application layer.However,owing to the structural complexity of the power system,the construction of the power IoT continues to face problems such as complex access management of massive heterogeneous equipment,diverse IoT protocol access methods,high concurrency of network communications,and weak data security protection.To address these issues,this study optimizes the existing architecture of the power IoT and designs an integrated management framework for the access of multi-source heterogeneous data in the power IoT,comprising cloud,pipe,edge,and terminal parts.It further reviews and analyzes the key technologies involved in the power IoT,such as the unified management of the physical model,high concurrent access,multi-protocol access,multi-source heterogeneous data storage management,and data security control,to provide a more flexible,efficient,secure,and easy-to-use solution for multi-source heterogeneous data access in the power IoT. 展开更多
关键词 Power Internet of Things Object model High concurrency access Zero trust mechanism multi-source heterogeneous data
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A cross-analysis framework formulti-source volunteered, crowdsourced, and authoritative geographic information: The case study of volunteered personal traces analysis against transport network data
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作者 Gloria Bordogna Steven Capelli +1 位作者 Daniele E.Ciriello Giuseppe Psaila 《Geo-Spatial Information Science》 SCIE CSCD 2018年第3期257-271,共15页
The paper discusses the need of a high-level query language to allow analysts,geographers and,in general,non-programmers to easily cross-analyze multi-source VGI created by means of apps,crowd-sourced data from social... The paper discusses the need of a high-level query language to allow analysts,geographers and,in general,non-programmers to easily cross-analyze multi-source VGI created by means of apps,crowd-sourced data from social networks and authoritative geo-referenced data,usually represented as JSON data sets(nowadays,the de facto standard for data exported by social networks).Since an easy to use high-level language for querying and manipulating collections of possibly geo-tagged JSON objects is still unavailable,we propose a truly declarative language,named J-CO-QL,that is based on a well-defined execution model.A plug-in for a GIS permits to visualize geo-tagged data sets stored in a NoSQL database such as MongoDB;furthermore,the same plug-in can be used to write and execute J-CO-QL queries on those databases.The paper introduces the language by exemplifying its operators within a real study case,the aim of which is to understand the mobility of people in the neighborhood of Bergamo city.Cross-analysis of data about transportation networks and VGI from travelers is performed,by means of J-CO-QL language,capable to manipulate and transform,combine and join possibly geo-tagged JSON objects,in order to produce new possibly geo-tagged JSON objects satisfying users’needs. 展开更多
关键词 Cross-analysis framework comparing VGI crowd-sourced and authoritative geographical data JSON data-sets declarative query language heterogeneous data-sets
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