Cloud storage is widely used by large companies to store vast amounts of data and files,offering flexibility,financial savings,and security.However,information shoplifting poses significant threats,potentially leading...Cloud storage is widely used by large companies to store vast amounts of data and files,offering flexibility,financial savings,and security.However,information shoplifting poses significant threats,potentially leading to poor performance and privacy breaches.Blockchain-based cognitive computing can help protect and maintain information security and privacy in cloud platforms,ensuring businesses can focus on business development.To ensure data security in cloud platforms,this research proposed a blockchain-based Hybridized Data Driven Cognitive Computing(HD2C)model.However,the proposed HD2C framework addresses breaches of the privacy information of mixed participants of the Internet of Things(IoT)in the cloud.HD2C is developed by combining Federated Learning(FL)with a Blockchain consensus algorithm to connect smart contracts with Proof of Authority.The“Data Island”problem can be solved by FL’s emphasis on privacy and lightning-fast processing,while Blockchain provides a decentralized incentive structure that is impervious to poisoning.FL with Blockchain allows quick consensus through smart member selection and verification.The HD2C paradigm significantly improves the computational processing efficiency of intelligent manufacturing.Extensive analysis results derived from IIoT datasets confirm HD2C superiority.When compared to other consensus algorithms,the Blockchain PoA’s foundational cost is significant.The accuracy and memory utilization evaluation results predict the total benefits of the system.In comparison to the values 0.004 and 0.04,the value of 0.4 achieves good accuracy.According to the experiment results,the number of transactions per second has minimal impact on memory requirements.The findings of this study resulted in the development of a brand-new IIoT framework based on blockchain technology.展开更多
With increasingly complex website structure and continuously advancing web technologies,accurate user clicks recognition from massive HTTP data,which is critical for web usage mining,becomes more difficult.In this pap...With increasingly complex website structure and continuously advancing web technologies,accurate user clicks recognition from massive HTTP data,which is critical for web usage mining,becomes more difficult.In this paper,we propose a dependency graph model to describe the relationships between web requests.Based on this model,we design and implement a heuristic parallel algorithm to distinguish user clicks with the assistance of cloud computing technology.We evaluate the proposed algorithm with real massive data.The size of the dataset collected from a mobile core network is 228.7GB.It covers more than three million users.The experiment results demonstrate that the proposed algorithm can achieve higher accuracy than previous methods.展开更多
Cloud computing technology is changing the development and usage patterns of IT infrastructure and applications. Virtualized and distributed systems as well as unified management and scheduling has greatly im proved c...Cloud computing technology is changing the development and usage patterns of IT infrastructure and applications. Virtualized and distributed systems as well as unified management and scheduling has greatly im proved computing and storage. Management has become easier, andOAM costs have been significantly reduced. Cloud desktop technology is develop ing rapidly. With this technology, users can flexibly and dynamically use virtual ma chine resources, companies＇ efficiency of using and allocating resources is greatly improved, and information security is ensured. In most existing virtual cloud desk top solutions, computing and storage are bound together, and data is stored as im age files. This limits the flexibility and expandability of systems and is insufficient for meetinz customers＇ requirements in different scenarios.展开更多
A data driven computational model that accounts for more than two material states has been presented in this work. Presented model can account for multiple state variables, such as stresses,strains, strain rates and f...A data driven computational model that accounts for more than two material states has been presented in this work. Presented model can account for multiple state variables, such as stresses,strains, strain rates and failure stress, as compared to previously reported models with two states.Model is used to perform deformation and failure simulations of carbon nanotubes and carbon nanotube/epoxy nanocomposites. The model capability of capturing the strain rate dependent deformation and failure has been demonstrated through predictions against uniaxial test data taken from literature. The predicted results show a good agreement between data set taken from literature and simulations.展开更多
This study proposesan over all framework for applying wireless manufacturing(WM)technologies in a smart factory and establishes a smart factory data computing and information using system (dc-IUS). Several plug-and-pl...This study proposesan over all framework for applying wireless manufacturing(WM)technologies in a smart factory and establishes a smart factory data computing and information using system (dc-IUS). Several plug-and-play (PnP) application modules of the dc-IUS are presented in the fields of machining process and quality control,material flow and inventory control,and factory resource tracking. Different schemes are discussed about how and where to apply these functions. Then some running examples are studied to demonstrate the feasibility and reliability of dc-IUS. At last,the challenges of applying WM are discussed and a conclusion is given.展开更多
With the growing popularity of data-intensive services on the Internet, the traditional process-centric model for business process meets challenges due to the lack of abilities to describe data semantics and dependenc...With the growing popularity of data-intensive services on the Internet, the traditional process-centric model for business process meets challenges due to the lack of abilities to describe data semantics and dependencies, resulting in the inflexibility of the design and implement for the processes. This paper proposes a novel data-aware business process model which is able to describe both explicit control flow and implicit data flow. Data model with dependencies which are formulated by Linear-time Temporal Logic(LTL) is presented, and their satisfiability is validated by an automaton-based model checking algorithm. Data dependencies are fully considered in modeling phase, which helps to improve the efficiency and reliability of programming during developing phase. Finally, a prototype system based on j BPM for data-aware workflow is designed using such model, and has been deployed to Beijing Kingfore heating management system to validate the flexibility, efficacy and convenience of our approach for massive coding and large-scale system management in reality.展开更多
In order to realize visualization of three-dimensional data field （TDDF） in instrument, two methods of visualization of TDDF and the usual manner of quick graphic and image processing are analyzed. And how to use Op...In order to realize visualization of three-dimensional data field （TDDF） in instrument, two methods of visualization of TDDF and the usual manner of quick graphic and image processing are analyzed. And how to use OpenGL technique and the characteristic of analyzed data to construct a TDDF, the ways of reality processing and interactive processing are described. Then the medium geometric element and a related realistic model are constructed by means of the first algorithm. Models obtained for attaching the third dimension in three-dimensional data field are presented. An example for TDDF realization of machine measuring is provided. The analysis of resultant graphic indicates that the three-dimensional graphics built by the method developed is featured by good reality, fast processing and strong interaction展开更多
Despite the multifaceted advantages of cloud computing,concerns about data leakage or abuse impedes its adoption for security-sensi tive tasks.Recent investigations have revealed that the risk of unauthorized data acc...Despite the multifaceted advantages of cloud computing,concerns about data leakage or abuse impedes its adoption for security-sensi tive tasks.Recent investigations have revealed that the risk of unauthorized data access is one of the biggest concerns of users of cloud-based services.Transparency and accountability for data managed in the cloud is necessary.Specifically,when using a cloudhost service,a user typically has to trust both the cloud service provider and cloud infrastructure provider to properly handling private data.This is a multi-party system.Three particular trust models can be used according to the credibility of these providers.This pa per describes techniques for preventing data leakage that can be used with these different models.展开更多
Globally,digital technology and the digital economy have propelled technological revolution and industrial change,and it has become one of the main grounds of international industrial competition.It was estimated that...Globally,digital technology and the digital economy have propelled technological revolution and industrial change,and it has become one of the main grounds of international industrial competition.It was estimated that the scale of China’s digital economy would reach 50 trillion yuan in 2022,accounting for more than 40%of GDP,presenting great market potential and room for the growth of the digital economy.With the rapid development of the digital economy,the state attaches great importance to the construction of digital infrastructure and has introduced a series of policies to promote the systematic development and large-scale deployment of digital infrastructure.In 2022 the Chinese government planned to build 8 arithmetic hubs and 10 national data center clusters nationwide.To proactively address the future demand for AI across various scenarios,there is a need for a well-structured computing power infrastructure.The data center,serving as the pivotal hub for computing power,has evolved from the conventional cloud center to a more intelligent computing center,allowing for a diversified convergence of computing power supply.Besides,the data center accommodates a diverse array of arithmetic business forms from customers,reflecting the multi-industry developmental trend.The arithmetic service platform is consistently broadening its scope,with ongoing optimization and innovation in the design scheme of machine room processes.The widespread application of submerged phase-change liquid cooling technology and cold plate cooling technology introduces a series of new challenges to the construction of digital infrastructure.This paper delves into the design objectives,industry considerations,layout,and other dimensions of a smart computing center and proposes a new-generation data center solution that is“flexible,resilient,green,and low-carbon.”展开更多
To solve the lag problem of the traditional storage technology in mass data storage and management,the application platform is designed and built for big data on Hadoop and data warehouse integration platform,which en...To solve the lag problem of the traditional storage technology in mass data storage and management,the application platform is designed and built for big data on Hadoop and data warehouse integration platform,which ensured the convenience for the management and usage of data.In order to break through the master node system bottlenecks,a storage system with better performance is designed through introduction of cloud computing technology,which adopts the design of master-slave distribution patterns by the network access according to the recent principle.Thus the burden of single access the master node is reduced.Also file block update strategy and fault recovery mechanism are provided to solve the management bottleneck problem of traditional storage system on the data update and fault recovery and offer feasible technical solutions to storage management for big data.展开更多
Intellectualization has become a new trend for telecom industry, driven by intelligent technology including cloud computing, big data, and Internet of things. In order to satisfy the service demand of intelligent logi...Intellectualization has become a new trend for telecom industry, driven by intelligent technology including cloud computing, big data, and Internet of things. In order to satisfy the service demand of intelligent logistics, this paper designed an intelligent logistics platform containing the main applications such as e-commerce, self-service transceiver, big data analysis, path location and distribution optimization. The intelligent logistics service platform has been built based on cloud computing to collect, store and handling multi-source heterogeneous mass data from sensors, RFID electronic tag, vehicle terminals and APP, so that the open-access cloud services including distribution, positioning, navigation, scheduling and other data services can be provided for the logistics distribution applications. And then the architecture of intelligent logistics cloud platform containing software layer(SaaS), platform layer(PaaS) and infrastructure(IaaS) has been constructed accordance with the core technology relative high concurrent processing technique, heterogeneous terminal data access, encapsulation and data mining. Therefore, intelligent logistics cloud platform can be carried out by the service mode for implementation to accelerate the construction of the symbiotic win-winlogistics ecological system and the benign development of the ICT industry in the trend of intellectualization in China.展开更多
The fast-growing demand of computational fluid dynamics（CFD） application for computing resources stimulates the development of high performance computing（HPC） and meanwhile raises new requirements for the technolo...The fast-growing demand of computational fluid dynamics（CFD） application for computing resources stimulates the development of high performance computing（HPC） and meanwhile raises new requirements for the technology of parallel application performance monitor and analysis.In response to large-scale and long-time running for the application of CFD,online and scalable performance analysis technology is required to optimize the parallel programs as well as to improve their operational efficiency.As a result,this research implements a scalable infrastructure for online performance analysis on CFD application with homogeneous or heterogeneous system.The infrastructure is part of the parallel application performance monitor and analysis system（PAPMAS） and is composed of two modules which are scalable data transmission module and data storage module.The paper analyzes and elaborates this infrastructure in detail with respect to its design and implementation.Furthermore,some experiments are carried out to verify the rationality and high efficiency of this infrastructure that could be adopted to meet the practical needs.展开更多
Data cube computation is an important problem in the field of data warehousing and OLAP （online analytical processing）. Although it has been studied extensively in the past, most of its algorithms are designed witho...Data cube computation is an important problem in the field of data warehousing and OLAP （online analytical processing）. Although it has been studied extensively in the past, most of its algorithms are designed without considering CPU and cache behavior. In this paper, we first propose a cache-conscious cubing approach called CC-Cubing to efficiently compute data cubes on a modern processor. This method can enhance CPU and cache performances. It adopts an integrated depth-first and breadth-first partitioning order and partitions multiple dimensions simultaneously. The partitioning scheme improves the data spatial locality and increases the utilization of cache lines. Software prefetching techniques are then applied in the sorting phase to hide the expensive cache misses associated with data scans. In addition, a cache-aware method is used in CC-Cubing to switch the sort algorithm dynamically. Our performance study shows that CC-Cubing outperforms BUC, Star-Cubing and MM-Cubing in most cases. Then, in order to fully utilize an SMT （simultaneous multithreading） processor, we present a thread-based CC-Cubing-SMT method. This parallel method provides an improvement up to 27% for the single-threaded CC-Cubing algorithm.展开更多
Cloud computing can significantly improve efficiency in Internet utilization and data management.Several cloud applications(file sharing,backup,data up/download etc.) imply transfers of large amount of data without re...Cloud computing can significantly improve efficiency in Internet utilization and data management.Several cloud applications(file sharing,backup,data up/download etc.) imply transfers of large amount of data without real-time requirements.In several use-cases cloud-computing solutions reduce operational costs and guarantee target QoS.These solutions become critical when satellite systems are utilized,since resources are limited,network latency is huge and bandwidth costs are high.Using satellite capacity for cloud-computing bulk traffic,keeping acceptable performance of interactive applications,is very important and can limit the connectivity costs.This goal can be achieved installing in the Set Top Box(STB) a proxy agent,to differentiate traffic and assign bandwidth according to priority,leaving spare capacity to bulk cloud computing traffic.This aim is typically reached using a specific QoS architecture,adding functional blocks at network or lower layers.We propose to manage such a process at transport layer only.The endpoint proxy implements a new transport protocol called TCP Noordwijk+,introducing a flow control differentiation capability.The proxy includes TPCN+ which efficiently transfers low-priority bulk data and handles interactive data,keeping a high degree of friendliness.The outcomes of Ns-2simulations confirm applicability and good performance of the proposed solution.展开更多
I provide some science and reflections from my experiences working in geophysics,along with connections to computational and data sciences,including recent developments in machine learning.I highlight several individu...I provide some science and reflections from my experiences working in geophysics,along with connections to computational and data sciences,including recent developments in machine learning.I highlight several individuals and groups who have influenced me,both through direct collaborations as well as from ideas and insights that I have learned from.While my reflections are rooted in geophysics,they should also be relevant to other computational scientific and engineering fields.I also provide some thoughts for young,applied scientists and engineers.展开更多
The paper is devoted to study of the electrical parameters of the motion parts of the MEMS such as solenoids. The analytical background is given in order to describe the influence of the electrical field components on...The paper is devoted to study of the electrical parameters of the motion parts of the MEMS such as solenoids. The analytical background is given in order to describe the influence of the electrical field components on the forces, which are result of interaction of the electromagnetic (EM) field components with the parts of motion devices of MEMS. The given analytical formulas open the ability to calculate the self-inductance of the microsolenoids of the different kind, as well as the stored energy of such motion devices, that could be used for the modeling and optimization of parameters of running devices of MEMS such as actuators, sensors etc.展开更多
文摘Cloud storage is widely used by large companies to store vast amounts of data and files,offering flexibility,financial savings,and security.However,information shoplifting poses significant threats,potentially leading to poor performance and privacy breaches.Blockchain-based cognitive computing can help protect and maintain information security and privacy in cloud platforms,ensuring businesses can focus on business development.To ensure data security in cloud platforms,this research proposed a blockchain-based Hybridized Data Driven Cognitive Computing(HD2C)model.However,the proposed HD2C framework addresses breaches of the privacy information of mixed participants of the Internet of Things(IoT)in the cloud.HD2C is developed by combining Federated Learning(FL)with a Blockchain consensus algorithm to connect smart contracts with Proof of Authority.The“Data Island”problem can be solved by FL’s emphasis on privacy and lightning-fast processing,while Blockchain provides a decentralized incentive structure that is impervious to poisoning.FL with Blockchain allows quick consensus through smart member selection and verification.The HD2C paradigm significantly improves the computational processing efficiency of intelligent manufacturing.Extensive analysis results derived from IIoT datasets confirm HD2C superiority.When compared to other consensus algorithms,the Blockchain PoA’s foundational cost is significant.The accuracy and memory utilization evaluation results predict the total benefits of the system.In comparison to the values 0.004 and 0.04,the value of 0.4 achieves good accuracy.According to the experiment results,the number of transactions per second has minimal impact on memory requirements.The findings of this study resulted in the development of a brand-new IIoT framework based on blockchain technology.
基金supported in part by the Fundamental Research Funds for the Central Universities under Grant No.2013RC0114111 Project of China under Grant No.B08004
文摘With increasingly complex website structure and continuously advancing web technologies,accurate user clicks recognition from massive HTTP data,which is critical for web usage mining,becomes more difficult.In this paper,we propose a dependency graph model to describe the relationships between web requests.Based on this model,we design and implement a heuristic parallel algorithm to distinguish user clicks with the assistance of cloud computing technology.We evaluate the proposed algorithm with real massive data.The size of the dataset collected from a mobile core network is 228.7GB.It covers more than three million users.The experiment results demonstrate that the proposed algorithm can achieve higher accuracy than previous methods.
文摘Cloud computing technology is changing the development and usage patterns of IT infrastructure and applications. Virtualized and distributed systems as well as unified management and scheduling has greatly im proved computing and storage. Management has become easier, andOAM costs have been significantly reduced. Cloud desktop technology is develop ing rapidly. With this technology, users can flexibly and dynamically use virtual ma chine resources, companies＇ efficiency of using and allocating resources is greatly improved, and information security is ensured. In most existing virtual cloud desk top solutions, computing and storage are bound together, and data is stored as im age files. This limits the flexibility and expandability of systems and is insufficient for meetinz customers＇ requirements in different scenarios.
文摘A data driven computational model that accounts for more than two material states has been presented in this work. Presented model can account for multiple state variables, such as stresses,strains, strain rates and failure stress, as compared to previously reported models with two states.Model is used to perform deformation and failure simulations of carbon nanotubes and carbon nanotube/epoxy nanocomposites. The model capability of capturing the strain rate dependent deformation and failure has been demonstrated through predictions against uniaxial test data taken from literature. The predicted results show a good agreement between data set taken from literature and simulations.
基金National Natural Science Foundation of China(No.50875204)National Basic Research "973" Project(No.2011CB706805)
文摘This study proposesan over all framework for applying wireless manufacturing(WM)technologies in a smart factory and establishes a smart factory data computing and information using system (dc-IUS). Several plug-and-play (PnP) application modules of the dc-IUS are presented in the fields of machining process and quality control,material flow and inventory control,and factory resource tracking. Different schemes are discussed about how and where to apply these functions. Then some running examples are studied to demonstrate the feasibility and reliability of dc-IUS. At last,the challenges of applying WM are discussed and a conclusion is given.
基金supported by the National Natural Science Foundation of China (No. 61502043, No. 61132001)Beijing Natural Science Foundation (No. 4162042)BeiJing Talents Fund (No. 2015000020124G082)
文摘With the growing popularity of data-intensive services on the Internet, the traditional process-centric model for business process meets challenges due to the lack of abilities to describe data semantics and dependencies, resulting in the inflexibility of the design and implement for the processes. This paper proposes a novel data-aware business process model which is able to describe both explicit control flow and implicit data flow. Data model with dependencies which are formulated by Linear-time Temporal Logic(LTL) is presented, and their satisfiability is validated by an automaton-based model checking algorithm. Data dependencies are fully considered in modeling phase, which helps to improve the efficiency and reliability of programming during developing phase. Finally, a prototype system based on j BPM for data-aware workflow is designed using such model, and has been deployed to Beijing Kingfore heating management system to validate the flexibility, efficacy and convenience of our approach for massive coding and large-scale system management in reality.
基金This project is supported by National Natural Science Foundation of China (No.50405009)
文摘In order to realize visualization of three-dimensional data field （TDDF） in instrument, two methods of visualization of TDDF and the usual manner of quick graphic and image processing are analyzed. And how to use OpenGL technique and the characteristic of analyzed data to construct a TDDF, the ways of reality processing and interactive processing are described. Then the medium geometric element and a related realistic model are constructed by means of the first algorithm. Models obtained for attaching the third dimension in three-dimensional data field are presented. An example for TDDF realization of machine measuring is provided. The analysis of resultant graphic indicates that the three-dimensional graphics built by the method developed is featured by good reality, fast processing and strong interaction
基金supported by National Basic Research (973) Program of China (2011CB302505)Natural Science Foundation of China (61373145, 61170210)+1 种基金National High-Tech R&D (863) Program of China (2012AA012600,2011AA01A203)Chinese Special Project of Science and Technology (2012ZX01039001)
文摘Despite the multifaceted advantages of cloud computing,concerns about data leakage or abuse impedes its adoption for security-sensi tive tasks.Recent investigations have revealed that the risk of unauthorized data access is one of the biggest concerns of users of cloud-based services.Transparency and accountability for data managed in the cloud is necessary.Specifically,when using a cloudhost service,a user typically has to trust both the cloud service provider and cloud infrastructure provider to properly handling private data.This is a multi-party system.Three particular trust models can be used according to the credibility of these providers.This pa per describes techniques for preventing data leakage that can be used with these different models.
文摘Globally,digital technology and the digital economy have propelled technological revolution and industrial change,and it has become one of the main grounds of international industrial competition.It was estimated that the scale of China’s digital economy would reach 50 trillion yuan in 2022,accounting for more than 40%of GDP,presenting great market potential and room for the growth of the digital economy.With the rapid development of the digital economy,the state attaches great importance to the construction of digital infrastructure and has introduced a series of policies to promote the systematic development and large-scale deployment of digital infrastructure.In 2022 the Chinese government planned to build 8 arithmetic hubs and 10 national data center clusters nationwide.To proactively address the future demand for AI across various scenarios,there is a need for a well-structured computing power infrastructure.The data center,serving as the pivotal hub for computing power,has evolved from the conventional cloud center to a more intelligent computing center,allowing for a diversified convergence of computing power supply.Besides,the data center accommodates a diverse array of arithmetic business forms from customers,reflecting the multi-industry developmental trend.The arithmetic service platform is consistently broadening its scope,with ongoing optimization and innovation in the design scheme of machine room processes.The widespread application of submerged phase-change liquid cooling technology and cold plate cooling technology introduces a series of new challenges to the construction of digital infrastructure.This paper delves into the design objectives,industry considerations,layout,and other dimensions of a smart computing center and proposes a new-generation data center solution that is“flexible,resilient,green,and low-carbon.”
文摘To solve the lag problem of the traditional storage technology in mass data storage and management,the application platform is designed and built for big data on Hadoop and data warehouse integration platform,which ensured the convenience for the management and usage of data.In order to break through the master node system bottlenecks,a storage system with better performance is designed through introduction of cloud computing technology,which adopts the design of master-slave distribution patterns by the network access according to the recent principle.Thus the burden of single access the master node is reduced.Also file block update strategy and fault recovery mechanism are provided to solve the management bottleneck problem of traditional storage system on the data update and fault recovery and offer feasible technical solutions to storage management for big data.
基金supported in part by National Key Research and Development Program under Grant No. 2016YFC0803206China Postdoctoral Science Foundation under Grant No.2016M600972
文摘Intellectualization has become a new trend for telecom industry, driven by intelligent technology including cloud computing, big data, and Internet of things. In order to satisfy the service demand of intelligent logistics, this paper designed an intelligent logistics platform containing the main applications such as e-commerce, self-service transceiver, big data analysis, path location and distribution optimization. The intelligent logistics service platform has been built based on cloud computing to collect, store and handling multi-source heterogeneous mass data from sensors, RFID electronic tag, vehicle terminals and APP, so that the open-access cloud services including distribution, positioning, navigation, scheduling and other data services can be provided for the logistics distribution applications. And then the architecture of intelligent logistics cloud platform containing software layer(SaaS), platform layer(PaaS) and infrastructure(IaaS) has been constructed accordance with the core technology relative high concurrent processing technique, heterogeneous terminal data access, encapsulation and data mining. Therefore, intelligent logistics cloud platform can be carried out by the service mode for implementation to accelerate the construction of the symbiotic win-winlogistics ecological system and the benign development of the ICT industry in the trend of intellectualization in China.
基金Aeronautical Science Foundation of China(2010ZA04001)National Natural Science Foundation of China (61073013,90818024)
文摘The fast-growing demand of computational fluid dynamics（CFD） application for computing resources stimulates the development of high performance computing（HPC） and meanwhile raises new requirements for the technology of parallel application performance monitor and analysis.In response to large-scale and long-time running for the application of CFD,online and scalable performance analysis technology is required to optimize the parallel programs as well as to improve their operational efficiency.As a result,this research implements a scalable infrastructure for online performance analysis on CFD application with homogeneous or heterogeneous system.The infrastructure is part of the parallel application performance monitor and analysis system（PAPMAS） and is composed of two modules which are scalable data transmission module and data storage module.The paper analyzes and elaborates this infrastructure in detail with respect to its design and implementation.Furthermore,some experiments are carried out to verify the rationality and high efficiency of this infrastructure that could be adopted to meet the practical needs.
基金supported in part by a grant from HP Labs China,the National Natural Science Foundation of China under GrantNo.60496325the Main Memory OLAP Servers Project
文摘Data cube computation is an important problem in the field of data warehousing and OLAP （online analytical processing）. Although it has been studied extensively in the past, most of its algorithms are designed without considering CPU and cache behavior. In this paper, we first propose a cache-conscious cubing approach called CC-Cubing to efficiently compute data cubes on a modern processor. This method can enhance CPU and cache performances. It adopts an integrated depth-first and breadth-first partitioning order and partitions multiple dimensions simultaneously. The partitioning scheme improves the data spatial locality and increases the utilization of cache lines. Software prefetching techniques are then applied in the sorting phase to hide the expensive cache misses associated with data scans. In addition, a cache-aware method is used in CC-Cubing to switch the sort algorithm dynamically. Our performance study shows that CC-Cubing outperforms BUC, Star-Cubing and MM-Cubing in most cases. Then, in order to fully utilize an SMT （simultaneous multithreading） processor, we present a thread-based CC-Cubing-SMT method. This parallel method provides an improvement up to 27% for the single-threaded CC-Cubing algorithm.
文摘Cloud computing can significantly improve efficiency in Internet utilization and data management.Several cloud applications(file sharing,backup,data up/download etc.) imply transfers of large amount of data without real-time requirements.In several use-cases cloud-computing solutions reduce operational costs and guarantee target QoS.These solutions become critical when satellite systems are utilized,since resources are limited,network latency is huge and bandwidth costs are high.Using satellite capacity for cloud-computing bulk traffic,keeping acceptable performance of interactive applications,is very important and can limit the connectivity costs.This goal can be achieved installing in the Set Top Box(STB) a proxy agent,to differentiate traffic and assign bandwidth according to priority,leaving spare capacity to bulk cloud computing traffic.This aim is typically reached using a specific QoS architecture,adding functional blocks at network or lower layers.We propose to manage such a process at transport layer only.The endpoint proxy implements a new transport protocol called TCP Noordwijk+,introducing a flow control differentiation capability.The proxy includes TPCN+ which efficiently transfers low-priority bulk data and handles interactive data,keeping a high degree of friendliness.The outcomes of Ns-2simulations confirm applicability and good performance of the proposed solution.
文摘I provide some science and reflections from my experiences working in geophysics,along with connections to computational and data sciences,including recent developments in machine learning.I highlight several individuals and groups who have influenced me,both through direct collaborations as well as from ideas and insights that I have learned from.While my reflections are rooted in geophysics,they should also be relevant to other computational scientific and engineering fields.I also provide some thoughts for young,applied scientists and engineers.
文摘The paper is devoted to study of the electrical parameters of the motion parts of the MEMS such as solenoids. The analytical background is given in order to describe the influence of the electrical field components on the forces, which are result of interaction of the electromagnetic (EM) field components with the parts of motion devices of MEMS. The given analytical formulas open the ability to calculate the self-inductance of the microsolenoids of the different kind, as well as the stored energy of such motion devices, that could be used for the modeling and optimization of parameters of running devices of MEMS such as actuators, sensors etc.
