In the heterogeneous power internet of things(IoT)environment,data signals are acquired to support different business systems to realize advanced intelligent applications,with massive,multi-source,heterogeneous and ot...In the heterogeneous power internet of things(IoT)environment,data signals are acquired to support different business systems to realize advanced intelligent applications,with massive,multi-source,heterogeneous and other characteristics.Reliable perception of information and efficient transmission of energy in multi-source heterogeneous environments are crucial issues.Compressive sensing(CS),as an effective method of signal compression and transmission,can accurately recover the original signal only by very few sampling.In this paper,we study a new method of multi-source heterogeneous data signal reconstruction of power IoT based on compressive sensing technology.Based on the traditional compressive sensing technology to directly recover multi-source heterogeneous signals,we fully use the interference subspace information to design the measurement matrix,which directly and effectively eliminates the interference while making the measurement.The measure matrix is optimized by minimizing the average cross-coherence of the matrix,and the reconstruction performance of the new method is further improved.Finally,the effectiveness of the new method with different parameter settings under different multi-source heterogeneous data signal cases is verified by using orthogonal matching pursuit(OMP)and sparsity adaptive matching pursuit(SAMP)for considering the actual environment with prior information utilization of signal sparsity and no prior information utilization of signal sparsity.展开更多
Due to the development of cloud computing and machine learning,users can upload their data to the cloud for machine learning model training.However,dishonest clouds may infer user data,resulting in user data leakage.P...Due to the development of cloud computing and machine learning,users can upload their data to the cloud for machine learning model training.However,dishonest clouds may infer user data,resulting in user data leakage.Previous schemes have achieved secure outsourced computing,but they suffer from low computational accuracy,difficult-to-handle heterogeneous distribution of data from multiple sources,and high computational cost,which result in extremely poor user experience and expensive cloud computing costs.To address the above problems,we propose amulti-precision,multi-sourced,andmulti-key outsourcing neural network training scheme.Firstly,we design a multi-precision functional encryption computation based on Euclidean division.Second,we design the outsourcing model training algorithm based on a multi-precision functional encryption with multi-sourced heterogeneity.Finally,we conduct experiments on three datasets.The results indicate that our framework achieves an accuracy improvement of 6%to 30%.Additionally,it offers a memory space optimization of 1.0×2^(24) times compared to the previous best approach.展开更多
With the acceleration of intelligent transformation of energy system,the monitoring of equipment operation status and optimization of production process in thermal power plants face the challenge of multi-source heter...With the acceleration of intelligent transformation of energy system,the monitoring of equipment operation status and optimization of production process in thermal power plants face the challenge of multi-source heterogeneous data integration.In view of the heterogeneous characteristics of physical sensor data,including temperature,vibration and pressure that generated by boilers,steam turbines and other key equipment and real-time working condition data of SCADA system,this paper proposes a multi-source heterogeneous data fusion and analysis platform for thermal power plants based on edge computing and deep learning.By constructing a multi-level fusion architecture,the platform adopts dynamic weight allocation strategy and 5D digital twin model to realize the collaborative analysis of physical sensor data,simulation calculation results and expert knowledge.The data fusion module combines Kalman filter,wavelet transform and Bayesian estimation method to solve the problem of data time series alignment and dimension difference.Simulation results show that the data fusion accuracy can be improved to more than 98%,and the calculation delay can be controlled within 500 ms.The data analysis module integrates Dymola simulation model and AERMOD pollutant diffusion model,supports the cascade analysis of boiler combustion efficiency prediction and flue gas emission monitoring,system response time is less than 2 seconds,and data consistency verification accuracy reaches 99.5%.展开更多
Aim To develop a heterogeneous database united system(HDBUS)that combines the local database of Oracle, Sybase and SQL server distributed on different server into a global database,and supports the global transaction...Aim To develop a heterogeneous database united system(HDBUS)that combines the local database of Oracle, Sybase and SQL server distributed on different server into a global database,and supports the global transaction management and parallel query over the Intranet Methods In the designing and implementation of HDBUS two important concepts heterogeneous tables join. Results and Conclu- tion The first concept can be used to process the parallel query of multiple database server, the second one is the key technology of heterogeneous is the key technology of heterogeneous distribute database.展开更多
The future usage of heterogeneous databases will consist of the WWW and CORBA environments. The integration of the WWW databases and CORBA standards are discussed. These two techniques need to merge together to make d...The future usage of heterogeneous databases will consist of the WWW and CORBA environments. The integration of the WWW databases and CORBA standards are discussed. These two techniques need to merge together to make distributed usage of heterogeneous databases user friendly. In an environment integrating WWW databases and CORBA technologies, CORBA can be used to access heterogeneous data sources in the internet. This kind of applications can achieve distributed transactions to assure data consistency and integrity. The application of this technology is with a good prospect.展开更多
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
The problem of sharing heterogeneous database for accessing different educational resources has to be considered. The study is carried out to realize the heterogeneous database sharing for educational resources using ...The problem of sharing heterogeneous database for accessing different educational resources has to be considered. The study is carried out to realize the heterogeneous database sharing for educational resources using multi-media educa-tional resources as the researching object. XML is applied as middleware for the practical requirements of education. The study has important practical significance for the intellectualization of educational and teaching resource platform.展开更多
This paper describes the access to, and the content, characteristics, and potential applications of the tropical cyclone(TC) database that is maintained and actively developed by the China Meteorological Administratio...This paper describes the access to, and the content, characteristics, and potential applications of the tropical cyclone(TC) database that is maintained and actively developed by the China Meteorological Administration, with the aim of facilitating its use in scientific research and operational services. This database records data relating to all TCs that have passed through the western North Pacific(WNP) and South China Sea(SCS) since 1949. TC data collection has expanded over recent decades via continuous TC monitoring using remote sensing and specialized field detection techniques,allowing collation of a multi-source TC database for the WNP and SCS that covers a long period, with wide coverage and many observational elements. This database now comprises a wide variety of information related to TCs, such as historical or real-time locations(i.e., best track and landfall), intensity, dynamic and thermal structures, wind strengths, precipitation amounts, and frequency. This database will support ongoing research into the processes and patterns associated with TC climatic activity and TC forecasting.展开更多
Effectively managing extensive,multi-source,and multi-level real-scene 3D models for responsive retrieval scheduling and rapid visualization in the Web environment is a significant challenge in the current development...Effectively managing extensive,multi-source,and multi-level real-scene 3D models for responsive retrieval scheduling and rapid visualization in the Web environment is a significant challenge in the current development of real-scene 3D applications in China.In this paper,we address this challenge by reorganizing spatial and temporal information into a 3D geospatial grid.It introduces the Global 3D Geocoding System(G_(3)DGS),leveraging neighborhood similarity and uniqueness for efficient storage,retrieval,updating,and scheduling of these models.A combination of G_(3)DGS and non-relational databases is implemented,enhancing data storage scalability and flexibility.Additionally,a model detail management scheduling strategy(TLOD)based on G_(3)DGS and an importance factor T is designed.Compared with mainstream commercial and open-source platforms,this method significantly enhances the loadable capacity of massive multi-source real-scene 3D models in the Web environment by 33%,improves browsing efficiency by 48%,and accelerates invocation speed by 40%.展开更多
With recent advancement on hardware technologies, new general-purpose high-performance devices have been widely adopted, such as the graphics processing unit （GPU） and solid state drive （SSD）. GPU may offer an ord...With recent advancement on hardware technologies, new general-purpose high-performance devices have been widely adopted, such as the graphics processing unit （GPU） and solid state drive （SSD）. GPU may offer an order of higher throughput for applications with massive data parallelism, compared with the multicore CPU. Moreover, new storage device SSD is also capable of offering a much higher I/O throughput and lower latency than a traditional hard disk device （HDD）. These new hardware devices can significantly boost the performance of many applications;thus the database community has been actively engaging in adopting them into database systems. However, the performance benefit cannot be easily reaped if the new hardwares are improperly used. In this paper, we propose Hetero-DB, a high-performance database system by exploiting both the characteristics of the database system and the special properties of the new hardware devices in system’s design and implementation. Hetero-DB develops a GPU-aware query execution engine with GPU device memory management and query scheduling mechanism to support concurrent query execution. Furthermore, with the SSD-HDD hybrid storage system, we redesign the storage engine by organizing HDD and SSD into a two-level caching hierarchy in Hetero-DB. To best utilize the hybrid hardware devices, the semantic information that is critical for storage I/O is identified and passed to the storage manager, which has a great potential to improve the e？ciency and performance. Hetero-DB aims to maximize the performance benefits of GPU and SSD, and demonstrates the effectiveness for designing next generation database systems.展开更多
基于接收信号强度指示(received signal strength indicator,RSSI)指纹的定位方法需要预先建立定位区域指纹库,传统静态采集指纹库的建立更新需要大量的人力和时间,并且定位一致性容易受终端差异(如指纹采集手机与定位手机硬件不同导致...基于接收信号强度指示(received signal strength indicator,RSSI)指纹的定位方法需要预先建立定位区域指纹库,传统静态采集指纹库的建立更新需要大量的人力和时间,并且定位一致性容易受终端差异(如指纹采集手机与定位手机硬件不同导致接收信号差异)影响,使得这种方法的大范围推广使用变得异常艰难。针对以上问题,通过移动行走过程中采集的RSSI指纹建立对应的移动采集指纹库,根据移动采集指纹特征构建特征向量,提出移动采集指纹稀疏特征表征,建立基于自适应压缩感知算法的指纹匹配室内定位模型。实验结果表明,指纹采集效率提升了90.83%,平均定位误差为1.96 m,均方根误差为2.75 m,定位一致性差异误差平均提高了32.67%。所提方法在指纹采集效率、定位精度及不同手机的定位一致性方面优于现有算法。展开更多
基金supported by National Natural Science Foundation of China(12174350)Science and Technology Project of State Grid Henan Electric Power Company(5217Q0240008).
文摘In the heterogeneous power internet of things(IoT)environment,data signals are acquired to support different business systems to realize advanced intelligent applications,with massive,multi-source,heterogeneous and other characteristics.Reliable perception of information and efficient transmission of energy in multi-source heterogeneous environments are crucial issues.Compressive sensing(CS),as an effective method of signal compression and transmission,can accurately recover the original signal only by very few sampling.In this paper,we study a new method of multi-source heterogeneous data signal reconstruction of power IoT based on compressive sensing technology.Based on the traditional compressive sensing technology to directly recover multi-source heterogeneous signals,we fully use the interference subspace information to design the measurement matrix,which directly and effectively eliminates the interference while making the measurement.The measure matrix is optimized by minimizing the average cross-coherence of the matrix,and the reconstruction performance of the new method is further improved.Finally,the effectiveness of the new method with different parameter settings under different multi-source heterogeneous data signal cases is verified by using orthogonal matching pursuit(OMP)and sparsity adaptive matching pursuit(SAMP)for considering the actual environment with prior information utilization of signal sparsity and no prior information utilization of signal sparsity.
基金supported by Natural Science Foundation of China(Nos.62303126,62362008,author Z.Z,https://www.nsfc.gov.cn/,accessed on 20 December 2024)Major Scientific and Technological Special Project of Guizhou Province([2024]014)+2 种基金Guizhou Provincial Science and Technology Projects(No.ZK[2022]General149) ,author Z.Z,https://kjt.guizhou.gov.cn/,accessed on 20 December 2024)The Open Project of the Key Laboratory of Computing Power Network and Information Security,Ministry of Education under Grant 2023ZD037,author Z.Z,https://www.gzu.edu.cn/,accessed on 20 December 2024)Open Research Project of the State Key Laboratory of Industrial Control Technology,Zhejiang University,China(No.ICT2024B25),author Z.Z,https://www.gzu.edu.cn/,accessed on 20 December 2024).
文摘Due to the development of cloud computing and machine learning,users can upload their data to the cloud for machine learning model training.However,dishonest clouds may infer user data,resulting in user data leakage.Previous schemes have achieved secure outsourced computing,but they suffer from low computational accuracy,difficult-to-handle heterogeneous distribution of data from multiple sources,and high computational cost,which result in extremely poor user experience and expensive cloud computing costs.To address the above problems,we propose amulti-precision,multi-sourced,andmulti-key outsourcing neural network training scheme.Firstly,we design a multi-precision functional encryption computation based on Euclidean division.Second,we design the outsourcing model training algorithm based on a multi-precision functional encryption with multi-sourced heterogeneity.Finally,we conduct experiments on three datasets.The results indicate that our framework achieves an accuracy improvement of 6%to 30%.Additionally,it offers a memory space optimization of 1.0×2^(24) times compared to the previous best approach.
文摘With the acceleration of intelligent transformation of energy system,the monitoring of equipment operation status and optimization of production process in thermal power plants face the challenge of multi-source heterogeneous data integration.In view of the heterogeneous characteristics of physical sensor data,including temperature,vibration and pressure that generated by boilers,steam turbines and other key equipment and real-time working condition data of SCADA system,this paper proposes a multi-source heterogeneous data fusion and analysis platform for thermal power plants based on edge computing and deep learning.By constructing a multi-level fusion architecture,the platform adopts dynamic weight allocation strategy and 5D digital twin model to realize the collaborative analysis of physical sensor data,simulation calculation results and expert knowledge.The data fusion module combines Kalman filter,wavelet transform and Bayesian estimation method to solve the problem of data time series alignment and dimension difference.Simulation results show that the data fusion accuracy can be improved to more than 98%,and the calculation delay can be controlled within 500 ms.The data analysis module integrates Dymola simulation model and AERMOD pollutant diffusion model,supports the cascade analysis of boiler combustion efficiency prediction and flue gas emission monitoring,system response time is less than 2 seconds,and data consistency verification accuracy reaches 99.5%.
文摘Aim To develop a heterogeneous database united system(HDBUS)that combines the local database of Oracle, Sybase and SQL server distributed on different server into a global database,and supports the global transaction management and parallel query over the Intranet Methods In the designing and implementation of HDBUS two important concepts heterogeneous tables join. Results and Conclu- tion The first concept can be used to process the parallel query of multiple database server, the second one is the key technology of heterogeneous is the key technology of heterogeneous distribute database.
文摘The future usage of heterogeneous databases will consist of the WWW and CORBA environments. The integration of the WWW databases and CORBA standards are discussed. These two techniques need to merge together to make distributed usage of heterogeneous databases user friendly. In an environment integrating WWW databases and CORBA technologies, CORBA can be used to access heterogeneous data sources in the internet. This kind of applications can achieve distributed transactions to assure data consistency and integrity. The application of this technology is with a good prospect.
基金supported by the National Key Research and Development Program of China(grant number 2019YFE0123600)。
文摘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.
文摘The problem of sharing heterogeneous database for accessing different educational resources has to be considered. The study is carried out to realize the heterogeneous database sharing for educational resources using multi-media educa-tional resources as the researching object. XML is applied as middleware for the practical requirements of education. The study has important practical significance for the intellectualization of educational and teaching resource platform.
基金supported by the Key Projects of the National Key R&D Program (Grant No. 2018YFC1506300)the Key Program for International S&T Cooperation Projects of China (Grant No. 2017YFE0107700)。
文摘This paper describes the access to, and the content, characteristics, and potential applications of the tropical cyclone(TC) database that is maintained and actively developed by the China Meteorological Administration, with the aim of facilitating its use in scientific research and operational services. This database records data relating to all TCs that have passed through the western North Pacific(WNP) and South China Sea(SCS) since 1949. TC data collection has expanded over recent decades via continuous TC monitoring using remote sensing and specialized field detection techniques,allowing collation of a multi-source TC database for the WNP and SCS that covers a long period, with wide coverage and many observational elements. This database now comprises a wide variety of information related to TCs, such as historical or real-time locations(i.e., best track and landfall), intensity, dynamic and thermal structures, wind strengths, precipitation amounts, and frequency. This database will support ongoing research into the processes and patterns associated with TC climatic activity and TC forecasting.
基金National Key Research and Development Program of China(No.2023YFB3907103).
文摘Effectively managing extensive,multi-source,and multi-level real-scene 3D models for responsive retrieval scheduling and rapid visualization in the Web environment is a significant challenge in the current development of real-scene 3D applications in China.In this paper,we address this challenge by reorganizing spatial and temporal information into a 3D geospatial grid.It introduces the Global 3D Geocoding System(G_(3)DGS),leveraging neighborhood similarity and uniqueness for efficient storage,retrieval,updating,and scheduling of these models.A combination of G_(3)DGS and non-relational databases is implemented,enhancing data storage scalability and flexibility.Additionally,a model detail management scheduling strategy(TLOD)based on G_(3)DGS and an importance factor T is designed.Compared with mainstream commercial and open-source platforms,this method significantly enhances the loadable capacity of massive multi-source real-scene 3D models in the Web environment by 33%,improves browsing efficiency by 48%,and accelerates invocation speed by 40%.
基金This work was supported in part by the National Science Foundation of USA under Grant Nos. CCF-0913050, OCI-1147522, and CNS-1162165.
文摘With recent advancement on hardware technologies, new general-purpose high-performance devices have been widely adopted, such as the graphics processing unit （GPU） and solid state drive （SSD）. GPU may offer an order of higher throughput for applications with massive data parallelism, compared with the multicore CPU. Moreover, new storage device SSD is also capable of offering a much higher I/O throughput and lower latency than a traditional hard disk device （HDD）. These new hardware devices can significantly boost the performance of many applications;thus the database community has been actively engaging in adopting them into database systems. However, the performance benefit cannot be easily reaped if the new hardwares are improperly used. In this paper, we propose Hetero-DB, a high-performance database system by exploiting both the characteristics of the database system and the special properties of the new hardware devices in system’s design and implementation. Hetero-DB develops a GPU-aware query execution engine with GPU device memory management and query scheduling mechanism to support concurrent query execution. Furthermore, with the SSD-HDD hybrid storage system, we redesign the storage engine by organizing HDD and SSD into a two-level caching hierarchy in Hetero-DB. To best utilize the hybrid hardware devices, the semantic information that is critical for storage I/O is identified and passed to the storage manager, which has a great potential to improve the e？ciency and performance. Hetero-DB aims to maximize the performance benefits of GPU and SSD, and demonstrates the effectiveness for designing next generation database systems.
