Energy crisis and climate change have become two seriously concerned issues universally. As a feasible solution, Global Energy Interconnection(GEI) has been highly praised and positively responded by the international...Energy crisis and climate change have become two seriously concerned issues universally. As a feasible solution, Global Energy Interconnection(GEI) has been highly praised and positively responded by the international community once proposed by China. From strategic conception to implementation, GEI development has entered a new phase of joint action now. Gathering and building a global grid database is a prerequisite for conducting research on GEI. Based on the requirement of global grid data management and application, combining with big data and geographic information technology, this paper studies the global grid data acquisition and analysis process, sorts out and designs the global grid database structure supporting GEI research, and builds a global grid database system.展开更多
Ocean temperature is an important physical variable in marine ecosystems,and ocean temperature prediction is an important research objective in ocean-related fields.Currently,one of the commonly used methods for ocean...Ocean temperature is an important physical variable in marine ecosystems,and ocean temperature prediction is an important research objective in ocean-related fields.Currently,one of the commonly used methods for ocean temperature prediction is based on data-driven,but research on this method is mostly limited to the sea surface,with few studies on the prediction of internal ocean temperature.Existing graph neural network-based methods usually use predefined graphs or learned static graphs,which cannot capture the dynamic associations among data.In this study,we propose a novel dynamic spatiotemporal graph neural network(DSTGN)to predict threedimensional ocean temperature(3D-OT),which combines static graph learning and dynamic graph learning to automatically mine two unknown dependencies between sequences based on the original 3D-OT data without prior knowledge.Temporal and spatial dependencies in the time series were then captured using temporal and graph convolutions.We also integrated dynamic graph learning,static graph learning,graph convolution,and temporal convolution into an end-to-end framework for 3D-OT prediction using time-series grid data.In this study,we conducted prediction experiments using high-resolution 3D-OT from the Copernicus global ocean physical reanalysis,with data covering the vertical variation of temperature from the sea surface to 1000 m below the sea surface.We compared five mainstream models that are commonly used for ocean temperature prediction,and the results showed that the method achieved the best prediction results at all prediction scales.展开更多
E lement- partition- based methods for visualization of 3D unstructured grid data are presented. First, partition schemes for common elements, including curvilinear tetrahedra, pentahedra, hexahedra, etc., are given, ...E lement- partition- based methods for visualization of 3D unstructured grid data are presented. First, partition schemes for common elements, including curvilinear tetrahedra, pentahedra, hexahedra, etc., are given, so that complex elements can be divided into several rectilinear tetrahedra, and the visualization processes can be simplified.Then, a slice method for cloud map and an iso-surface method based on the partition schemes are described.展开更多
Recent studies have demonstrated the importance of LUCC change with climate and ecosystem simulation, but the result could only be determined precisely if a high-resolution underlying land cover map is used. While the...Recent studies have demonstrated the importance of LUCC change with climate and ecosystem simulation, but the result could only be determined precisely if a high-resolution underlying land cover map is used. While the efforts based satellites have provided a good baseline for present land cover, what the next advancement in the research about LUCC change required is the development of reconstruction of historical LUCC change especially spatially-explicit historical dataset. Being different from other similar studies, this study is based on the analysis of historical land use patterns in the traditional cultivated region of China. Taking no account of the less important factors, altitude, slope and population patterns are selected as the major drivers of reclamation in ancient China, and used to design the HCGM （Historical Cropland Gridding Model, at a 60 km×60 km resolution）, which is an empirical model for allocating the historical cropland inventory data spatially to grid cells in each political unit. Then we use this model to reconstruct cropland distribution of the study area in 1820, and verify the result by prefectural cropland data of 1820, which is from the historical documents. The statistical analyzing result shows that the model can simulate the patterns of the cropland distribution in the historical period in the traditional cultivated region efficiently.展开更多
This paper describes the architecture of global distributed storage system for data grid. It focue on the management and the capability for the maximum users and maximum resources on the Internet, as well as performan...This paper describes the architecture of global distributed storage system for data grid. It focue on the management and the capability for the maximum users and maximum resources on the Internet, as well as performance and other issues.展开更多
A new method for constructing contours from complicated terrain elevation grids containing invalid data is put forward. By using this method, the topological consistency of contours in groups can be maintained effecti...A new method for constructing contours from complicated terrain elevation grids containing invalid data is put forward. By using this method, the topological consistency of contours in groups can be maintained effectively and the contours can be drawn smoothly based on boundaries pre-searching and local correction. An experimental example is given to demonstrate that the contours constructed by this method are of good quality.展开更多
This paper proposed a novel multilevel data cache model by Web cache （MDWC） based on network cost in data grid. By constructing a communicating tree of grid sites based on network cost and using a single leader for ...This paper proposed a novel multilevel data cache model by Web cache （MDWC） based on network cost in data grid. By constructing a communicating tree of grid sites based on network cost and using a single leader for each data segment within each region, the MDWC makes the most use of the Web cache of other sites whose bandwidth is as broad as covering the job executing site. The experiment result indicates that the MDWC reduces data response time and data update cost by avoiding network congestions while designing on the parameters concluded by the environment of application.展开更多
Dynamic data replication is a technique used in data grid environments that helps to reduce access latency and network bandwidth utilization. Replication also increases data availability thereby enhancing system relia...Dynamic data replication is a technique used in data grid environments that helps to reduce access latency and network bandwidth utilization. Replication also increases data availability thereby enhancing system reliability. In this paper we discuss the issues with single-location strategies in large-scale data integration applications, and examine potential multiple-location schemes. Dynamic multiple-location replication is NP-complete in nature. We therefore transform the multiple-location problem into several classical mathematical problems with different parameter settings, to which efficient approximation algorithms apply experimental results indicate that unlike single-location strategies our multiple-location schemes are efficient with respect to access latency and bandwidth consumption, especially when the requesters of a data set are distributed over a large scale of locations.展开更多
Sensor nodes in a wireless sensor network （WSN） are typically powered by batteries, thus the energy is constrained. It is our design goal to efficiently utilize the energy of each sensor node to extend its lifetime,...Sensor nodes in a wireless sensor network （WSN） are typically powered by batteries, thus the energy is constrained. It is our design goal to efficiently utilize the energy of each sensor node to extend its lifetime, so as to prolong the lifetime of the whole WSN. In this paper, we propose a path-based data aggregation scheme （PBDAS） for grid-based wireless sensor networks. In order to extend the lifetime of a WSN, we construct a grid infrastructure by partitioning the whole sensor field into a grid of cells. Each cell has a head responsible for aggregating its own data with the data sensed by the others in the same cell and then transmitting out. In order to efficiently and rapidly transmit the data to the base station （BS）, we link each cell head to form a chain. Each cell head on the chain takes turn becoming the chain leader responsible for transmitting data to the BS. Aggregated data moves from head to head along the chain, and finally the chain leader transmits to the BS. In PBDAS, only the cell heads need to transmit data toward the BS. Therefore, the data transmissions to the BS substantially decrease. Besides, the cell heads and chain leader are designated in turn according to the energy level so that the energy depletion of nodes is evenly distributed. Simulation results show that the proposed PBDAS extends the lifetime of sensor nodes, so as to make the lifetime of the whole network longer.展开更多
Neutral beam injection is one of the effective auxiliary heating methods in magnetic-confinementfusion experiments. In order to acquire the suppressor-grid current signal and avoid the grid being damaged by overheatin...Neutral beam injection is one of the effective auxiliary heating methods in magnetic-confinementfusion experiments. In order to acquire the suppressor-grid current signal and avoid the grid being damaged by overheating, a data acquisition and over-current protection system based on the PXI（PCI e Xtensions for Instrumentation） platform has been developed. The system consists of a current sensor, data acquisition module and over-current protection module. In the data acquisition module,the acquired data of one shot will be transferred in isolation and saved in a data-storage server in a txt file. It can also be recalled using NBWave for future analysis. The over-current protection module contains two modes： remote and local. This gives it the function of setting a threshold voltage remotely and locally, and the forbidden time of over-current protection also can be set by a host PC in remote mode. Experimental results demonstrate that the data acquisition and overcurrent protection system has the advantages of setting forbidden time and isolation transmission.展开更多
In existing web services-based workflow, data exchanging across the web services is centralized, the workflow engine intermediates at each step of the application sequence. However, many grid applications, especially ...In existing web services-based workflow, data exchanging across the web services is centralized, the workflow engine intermediates at each step of the application sequence. However, many grid applications, especially data intensive scientific applications, require exchanging large amount of data across the grid services. Having a central workflow engine relay the data between the services would resu＇lts in a bottleneck in these cases. This paper proposes a data exchange model for individual grid workflow and multiworkflows composition respectively. The model enables direct communication for large amounts of data between two grid services. To enable data to exchange among multiple workflows, the bridge data service is used.展开更多
Traditional grid computing focuses on the movement of data to compute resources and the management of large scale simulations. Data grid computing focuses on moving the operations to the storage location and on operat...Traditional grid computing focuses on the movement of data to compute resources and the management of large scale simulations. Data grid computing focuses on moving the operations to the storage location and on operations on data collections. We present three types of data grid operations that facilitate data driven research: the manipulation of time series data, the reproducible execution of workflows, and the mapping of data access to software-defined networks. These data grid operations have been implemented as operations on collections within the NSF DataNet Federation Consortium project. The operations can be applied at the remote resource where data are stored, improving the ability of researchers to interact with large collections.展开更多
The dispatching center of power-grid companies is also the data center of the power grid where gathers great amount of operating information. The valuable information contained in these data means a lot for power grid...The dispatching center of power-grid companies is also the data center of the power grid where gathers great amount of operating information. The valuable information contained in these data means a lot for power grid operating management, but at present there is no special method for the management of operating data resource. This paper introduces the operating analysis and data mining system for power grid dispatching. The technique of data warehousing online analytical processing has been used to manage and analysis the great capacity of data. This analysis system is based on the real-time data of the power grid to dig out the potential rule of the power grid operating. This system also provides a research platform for the dispatchers, help to improve the JIT (Just in Time) management of power system.展开更多
The Data Platform of Resource and Environment—whose data mainly come from field observation stations,spatial observations,and internet service institutions—is the base of data analysis and model simulation in geosci...The Data Platform of Resource and Environment—whose data mainly come from field observation stations,spatial observations,and internet service institutions—is the base of data analysis and model simulation in geoscience research in China.Among this integrated data platform,the tasks of the data platform of field observation stations are principally data collection,management,assimilation,and share service.Taking into consideration the distributing characteristics of the data sources and the service objects,the authors formulated the framework of the field observation stations' data platform based on the grid technology and designed its operating processes.The authors have further defined and analyzed the key functions and implementing techniques for each module.In a Linux operating system,validation tests for the data platform's function on data replication,data synchronization,and unified data service have been conducted under an environment that of the simulating field stations.展开更多
In this paper, we propose multi-characteristics based data scheduling over smart grid. Three different pricing strategies are presented based on user priority and load rate. Then the corresponding novel scheduling alg...In this paper, we propose multi-characteristics based data scheduling over smart grid. Three different pricing strategies are presented based on user priority and load rate. Then the corresponding novel scheduling algorithms are introduced by the proposed data priority and pricing strategies. The simulation experiments are carried out to evaluate the proposed algorithms based on trace data. And the results show that our methods can outperform the conventional method.展开更多
Recently, researches on distributed data mining by making use of grid are in trend. This paper introduces a data mining algorithm by means of distributed decision-tree,which has taken the advantage of conveniences and...Recently, researches on distributed data mining by making use of grid are in trend. This paper introduces a data mining algorithm by means of distributed decision-tree,which has taken the advantage of conveniences and services supplied by the computing platform-grid,and can perform a data mining of distributed classification on grid.展开更多
The Internet technology has already changed the Information Society in profound ways, and will continue to do so. Nowadays many people foresee that there is a similar trajectory for the next generation of Internet - G...The Internet technology has already changed the Information Society in profound ways, and will continue to do so. Nowadays many people foresee that there is a similar trajectory for the next generation of Internet - Grid Technology. As an emerging computational and networking infrastructure, Grid Computing is designed to provide pervasive, uniform and reliable access to data, computational and human resources distributed in a dynamic, heterogeneous environment. On the other hand, the development of Geographic Information System （GIS） has been highly influenced by the evolution of information technology such as the Internet, telecommunications, software and various types of computing technology. In particular, in the distributed GIS domain, the development However, due to the closed and centralized has made significant impact in the past decade. legacy of the architecture and the lack of interoperability, modularity, and flexibility, current distributed GIS still cannot fully accommodate the distributed, dynamic, heterogeneous and speedy development in network and computing environments. Hence, the development of a high performance distributed GIS system is still a challenging task. So, the development of Grid computing technology undoubtedly provides a unique opportunity for distributed GIS, and a Grid Computing based GIS paradigm becomes inevitable. This paper proposes a new computing platform based distributed GIS framework - the Grid Geographic Information System （G^2IS）.展开更多
文摘Energy crisis and climate change have become two seriously concerned issues universally. As a feasible solution, Global Energy Interconnection(GEI) has been highly praised and positively responded by the international community once proposed by China. From strategic conception to implementation, GEI development has entered a new phase of joint action now. Gathering and building a global grid database is a prerequisite for conducting research on GEI. Based on the requirement of global grid data management and application, combining with big data and geographic information technology, this paper studies the global grid data acquisition and analysis process, sorts out and designs the global grid database structure supporting GEI research, and builds a global grid database system.
基金The National Key R&D Program of China under contract No.2021YFC3101603.
文摘Ocean temperature is an important physical variable in marine ecosystems,and ocean temperature prediction is an important research objective in ocean-related fields.Currently,one of the commonly used methods for ocean temperature prediction is based on data-driven,but research on this method is mostly limited to the sea surface,with few studies on the prediction of internal ocean temperature.Existing graph neural network-based methods usually use predefined graphs or learned static graphs,which cannot capture the dynamic associations among data.In this study,we propose a novel dynamic spatiotemporal graph neural network(DSTGN)to predict threedimensional ocean temperature(3D-OT),which combines static graph learning and dynamic graph learning to automatically mine two unknown dependencies between sequences based on the original 3D-OT data without prior knowledge.Temporal and spatial dependencies in the time series were then captured using temporal and graph convolutions.We also integrated dynamic graph learning,static graph learning,graph convolution,and temporal convolution into an end-to-end framework for 3D-OT prediction using time-series grid data.In this study,we conducted prediction experiments using high-resolution 3D-OT from the Copernicus global ocean physical reanalysis,with data covering the vertical variation of temperature from the sea surface to 1000 m below the sea surface.We compared five mainstream models that are commonly used for ocean temperature prediction,and the results showed that the method achieved the best prediction results at all prediction scales.
文摘E lement- partition- based methods for visualization of 3D unstructured grid data are presented. First, partition schemes for common elements, including curvilinear tetrahedra, pentahedra, hexahedra, etc., are given, so that complex elements can be divided into several rectilinear tetrahedra, and the visualization processes can be simplified.Then, a slice method for cloud map and an iso-surface method based on the partition schemes are described.
基金Natiional Natural Science Foundation of China,No.40471007Innovation Knowledge Project of CAS,No.KZCX2-YW-315
文摘Recent studies have demonstrated the importance of LUCC change with climate and ecosystem simulation, but the result could only be determined precisely if a high-resolution underlying land cover map is used. While the efforts based satellites have provided a good baseline for present land cover, what the next advancement in the research about LUCC change required is the development of reconstruction of historical LUCC change especially spatially-explicit historical dataset. Being different from other similar studies, this study is based on the analysis of historical land use patterns in the traditional cultivated region of China. Taking no account of the less important factors, altitude, slope and population patterns are selected as the major drivers of reclamation in ancient China, and used to design the HCGM （Historical Cropland Gridding Model, at a 60 km×60 km resolution）, which is an empirical model for allocating the historical cropland inventory data spatially to grid cells in each political unit. Then we use this model to reconstruct cropland distribution of the study area in 1820, and verify the result by prefectural cropland data of 1820, which is from the historical documents. The statistical analyzing result shows that the model can simulate the patterns of the cropland distribution in the historical period in the traditional cultivated region efficiently.
文摘This paper describes the architecture of global distributed storage system for data grid. It focue on the management and the capability for the maximum users and maximum resources on the Internet, as well as performance and other issues.
文摘A new method for constructing contours from complicated terrain elevation grids containing invalid data is put forward. By using this method, the topological consistency of contours in groups can be maintained effectively and the contours can be drawn smoothly based on boundaries pre-searching and local correction. An experimental example is given to demonstrate that the contours constructed by this method are of good quality.
基金Supported by SEC E-Institute :Shanghai HighIn-stitutions Grid Project
文摘This paper proposed a novel multilevel data cache model by Web cache （MDWC） based on network cost in data grid. By constructing a communicating tree of grid sites based on network cost and using a single leader for each data segment within each region, the MDWC makes the most use of the Web cache of other sites whose bandwidth is as broad as covering the job executing site. The experiment result indicates that the MDWC reduces data response time and data update cost by avoiding network congestions while designing on the parameters concluded by the environment of application.
基金the National Natural Science Foundation of China (70671011)the National High-Technology Research and Development Program of China (863 Program) (2007AA04Z1B1)the Social Science Youth Foundation of Chongqing University ( CDSK2007-37)
文摘Dynamic data replication is a technique used in data grid environments that helps to reduce access latency and network bandwidth utilization. Replication also increases data availability thereby enhancing system reliability. In this paper we discuss the issues with single-location strategies in large-scale data integration applications, and examine potential multiple-location schemes. Dynamic multiple-location replication is NP-complete in nature. We therefore transform the multiple-location problem into several classical mathematical problems with different parameter settings, to which efficient approximation algorithms apply experimental results indicate that unlike single-location strategies our multiple-location schemes are efficient with respect to access latency and bandwidth consumption, especially when the requesters of a data set are distributed over a large scale of locations.
基金supported by the NSC under Grant No.NSC-101-2221-E-239-032 and NSC-102-2221-E-239-020
文摘Sensor nodes in a wireless sensor network （WSN） are typically powered by batteries, thus the energy is constrained. It is our design goal to efficiently utilize the energy of each sensor node to extend its lifetime, so as to prolong the lifetime of the whole WSN. In this paper, we propose a path-based data aggregation scheme （PBDAS） for grid-based wireless sensor networks. In order to extend the lifetime of a WSN, we construct a grid infrastructure by partitioning the whole sensor field into a grid of cells. Each cell has a head responsible for aggregating its own data with the data sensed by the others in the same cell and then transmitting out. In order to efficiently and rapidly transmit the data to the base station （BS）, we link each cell head to form a chain. Each cell head on the chain takes turn becoming the chain leader responsible for transmitting data to the BS. Aggregated data moves from head to head along the chain, and finally the chain leader transmits to the BS. In PBDAS, only the cell heads need to transmit data toward the BS. Therefore, the data transmissions to the BS substantially decrease. Besides, the cell heads and chain leader are designated in turn according to the energy level so that the energy depletion of nodes is evenly distributed. Simulation results show that the proposed PBDAS extends the lifetime of sensor nodes, so as to make the lifetime of the whole network longer.
基金supported by National Natural Science Foundation of China(No.11575240)Key Program of Research and Development of Hefei Science Center,CAS(grant 2016HSC-KPRD002)
文摘Neutral beam injection is one of the effective auxiliary heating methods in magnetic-confinementfusion experiments. In order to acquire the suppressor-grid current signal and avoid the grid being damaged by overheating, a data acquisition and over-current protection system based on the PXI（PCI e Xtensions for Instrumentation） platform has been developed. The system consists of a current sensor, data acquisition module and over-current protection module. In the data acquisition module,the acquired data of one shot will be transferred in isolation and saved in a data-storage server in a txt file. It can also be recalled using NBWave for future analysis. The over-current protection module contains two modes： remote and local. This gives it the function of setting a threshold voltage remotely and locally, and the forbidden time of over-current protection also can be set by a host PC in remote mode. Experimental results demonstrate that the data acquisition and overcurrent protection system has the advantages of setting forbidden time and isolation transmission.
基金Supported by the National Natural Science Foun-dation of China(60373072)
文摘In existing web services-based workflow, data exchanging across the web services is centralized, the workflow engine intermediates at each step of the application sequence. However, many grid applications, especially data intensive scientific applications, require exchanging large amount of data across the grid services. Having a central workflow engine relay the data between the services would resu＇lts in a bottleneck in these cases. This paper proposes a data exchange model for individual grid workflow and multiworkflows composition respectively. The model enables direct communication for large amounts of data between two grid services. To enable data to exchange among multiple workflows, the bridge data service is used.
文摘Traditional grid computing focuses on the movement of data to compute resources and the management of large scale simulations. Data grid computing focuses on moving the operations to the storage location and on operations on data collections. We present three types of data grid operations that facilitate data driven research: the manipulation of time series data, the reproducible execution of workflows, and the mapping of data access to software-defined networks. These data grid operations have been implemented as operations on collections within the NSF DataNet Federation Consortium project. The operations can be applied at the remote resource where data are stored, improving the ability of researchers to interact with large collections.
文摘The dispatching center of power-grid companies is also the data center of the power grid where gathers great amount of operating information. The valuable information contained in these data means a lot for power grid operating management, but at present there is no special method for the management of operating data resource. This paper introduces the operating analysis and data mining system for power grid dispatching. The technique of data warehousing online analytical processing has been used to manage and analysis the great capacity of data. This analysis system is based on the real-time data of the power grid to dig out the potential rule of the power grid operating. This system also provides a research platform for the dispatchers, help to improve the JIT (Just in Time) management of power system.
基金supported by the Incubation Foundation for Special Disciplines of National Science Foundation of China (NSFC) (grant number: J0630966)Chinese Research Network on Special Environment and Disaster (CRENSED) of Ministry of Science and Technology of the People’s Republic of China (grant number:1Z2005DKA10600)the Knowledge Innovation Important Program of Chinese Academy of Sciences (Grant Number:NF105-SDB-1-21)
文摘The Data Platform of Resource and Environment—whose data mainly come from field observation stations,spatial observations,and internet service institutions—is the base of data analysis and model simulation in geoscience research in China.Among this integrated data platform,the tasks of the data platform of field observation stations are principally data collection,management,assimilation,and share service.Taking into consideration the distributing characteristics of the data sources and the service objects,the authors formulated the framework of the field observation stations' data platform based on the grid technology and designed its operating processes.The authors have further defined and analyzed the key functions and implementing techniques for each module.In a Linux operating system,validation tests for the data platform's function on data replication,data synchronization,and unified data service have been conducted under an environment that of the simulating field stations.
基金supported in part by the Fundamental Key Research Project of Shanghai Municipal Science and Technology Commission(No.12JC1404201)
文摘In this paper, we propose multi-characteristics based data scheduling over smart grid. Three different pricing strategies are presented based on user priority and load rate. Then the corresponding novel scheduling algorithms are introduced by the proposed data priority and pricing strategies. The simulation experiments are carried out to evaluate the proposed algorithms based on trace data. And the results show that our methods can outperform the conventional method.
文摘Recently, researches on distributed data mining by making use of grid are in trend. This paper introduces a data mining algorithm by means of distributed decision-tree,which has taken the advantage of conveniences and services supplied by the computing platform-grid,and can perform a data mining of distributed classification on grid.
文摘The Internet technology has already changed the Information Society in profound ways, and will continue to do so. Nowadays many people foresee that there is a similar trajectory for the next generation of Internet - Grid Technology. As an emerging computational and networking infrastructure, Grid Computing is designed to provide pervasive, uniform and reliable access to data, computational and human resources distributed in a dynamic, heterogeneous environment. On the other hand, the development of Geographic Information System （GIS） has been highly influenced by the evolution of information technology such as the Internet, telecommunications, software and various types of computing technology. In particular, in the distributed GIS domain, the development However, due to the closed and centralized has made significant impact in the past decade. legacy of the architecture and the lack of interoperability, modularity, and flexibility, current distributed GIS still cannot fully accommodate the distributed, dynamic, heterogeneous and speedy development in network and computing environments. Hence, the development of a high performance distributed GIS system is still a challenging task. So, the development of Grid computing technology undoubtedly provides a unique opportunity for distributed GIS, and a Grid Computing based GIS paradigm becomes inevitable. This paper proposes a new computing platform based distributed GIS framework - the Grid Geographic Information System （G^2IS）.
