With the advent of the digital economy,there has been a rapid proliferation of small-scale Internet data centers(SIDCs).By leveraging their spatiotemporal load regulation potential through data workload balancing,aggr...With the advent of the digital economy,there has been a rapid proliferation of small-scale Internet data centers(SIDCs).By leveraging their spatiotemporal load regulation potential through data workload balancing,aggregated SIDCs have emerged as promising demand response(DR)resources for future power distribution systems.This paper presents an innovative framework for assessing capacity value(CV)by aggregating SIDCs participating in DR programs(SIDC-DR).Initially,we delineate the concept of CV tailored for aggregated SIDC scenarios and establish a metric for the assessment.Considering the effects of the data load dynamics,equipment constraints,and user behavior,we developed a sophisticated DR model for aggregated SIDCs using a data network aggregation method.Unlike existing studies,the proposed model captures the uncertainties associated with end tenant decisions to opt into an SIDC-DR program by utilizing a novel uncertainty modeling approach called Z-number formulation.This approach accounts for both the uncertainty in user participation intentions and the reliability of basic information during the DR process,enabling high-resolution profiling of the SIDC-DR potential in the CV evaluation.Simulation results from numerical studies conducted on a modified IEEE-33 node distribution system confirmed the effectiveness of the proposed approach and highlighted the potential benefits of SIDC-DR utilization in the efficient operation of future power systems.展开更多
Internet data center buildings have great importance for maintaining the post-earthquake functionality of telecommunication networks.It is essential to maintain the functionality of internet data center buildings duri...Internet data center buildings have great importance for maintaining the post-earthquake functionality of telecommunication networks.It is essential to maintain the functionality of internet data center buildings during earthquakes or recover immediately after earthquakes,which is referred to as seismic resilience.In this study,a seismic resilience assessment framework based on the Chinese code GB/T 38591-2020 is introduced first.The seismic damage and post-earthquake repair of both structural components and non-structural components are considered in the resilience assessment framework.A method for post-earthquake functionality loss quantification is proposed based on damage state and functionality loss of component.The subsystem level and system level functionality loss can be obtained by an integration principle.The seismic resilience of a typical internet data center building was evaluated to demonstrate the effectiveness of the proposed method.To enhance the seismic resilience level,different disaster mitigation techniques including the energy dissipation technology using buckling restrained braces and the base-isolation technology using lead-rubber bearings are adopted.The seismic resilience is quantified and the corresponding seismic resilience curves under different earthquake intensities are developed based on evaluation results.展开更多
Energy generation and consumption are the main aspects of social life due to the fact that modern people’s necessity for energy is a crucial ingredient for existence. Therefore, energy efficiency is regarded as the b...Energy generation and consumption are the main aspects of social life due to the fact that modern people’s necessity for energy is a crucial ingredient for existence. Therefore, energy efficiency is regarded as the best economical approach to provide safer and affordable energy for both utilities and consumers, through the enhancement of energy security and reduction of energy emissions. One of the problems of cloud computing service providers is the high rise in the cost of energy, efficiency together with carbon emission with regards to the running of their internet data centres (IDCs). In order to mitigate these issues, smart micro-grid was found to be suitable in increasing the energy efficiency, sustainability together with the reliability of electrical services for the IDCs. Therefore, this paper presents idea on how smart micro-grids can bring down the disturbing cost of energy, carbon emission by the IDCs with some level of energy efficiency all in an effort to attain green cloud computing services from the service providers. In specific term, we aim at achieving green information and communication technology (ICT) in the field of cloud computing in relations to energy efficiency, cost-effectiveness and carbon emission reduction from cloud data center’s perspective.展开更多
Influenza,an acute respiratory infectious disease caused by the influenza virus,exhibits distinct seasonal patterns in China,with peak activity occurring in winter and spring in northern regions,and in winter and summ...Influenza,an acute respiratory infectious disease caused by the influenza virus,exhibits distinct seasonal patterns in China,with peak activity occurring in winter and spring in northern regions,and in winter and summer in southern areas[1].The World Health Organization(WHO)emphasizes that early warning and epidemic intensity assessments are critical public health strategies for influenza prevention and control.Internet-based flu surveillance,with real-time data and low costs,effectively complements traditional methods.The Baidu Search Index,which reflects flu-related queries,strongly correlates with influenza trends,aiding in regional activity assessment and outbreak tracking[2].展开更多
The development of cloud computing has accel-erated the worldwide growth of internet data centers(IDCs).While a large portion of the energy consumption generated by intense computation introduces greater operation exp...The development of cloud computing has accel-erated the worldwide growth of internet data centers(IDCs).While a large portion of the energy consumption generated by intense computation introduces greater operation expenditures to the IDC enterprises.To manage the overall costs and utilize resources to their fullest extent,this paper introduces the concept of spatio-temporal workload allocation among the geographically distributed IDCs within a cloud,with the guarantee of the workload completion time and the consideration of computing service delay penalties by introducing the cost of inconvenience.Apart from the effort of the workload migration,the spatio-temporal variance of the renewable energies in the data center microgrids(DMGs)is fully considered in this paper.What's more,as the power consumed by the IDCs are primarily converted into heat,the waste heat recovery process is embedded in each IDC to demonstrate the effectiveness of the repurposed heat,which can be used by the residential heating demand in the thermal system,for total cost reduction and energy usage efficiency in the whole operating system.Applying real-life data traces of the electricity price,renewable energies and heating demand,these extensive evaluations demonstrate that both spatial and temporal complementary attempts on the supply side and demand side,along with power and thermal complementary efforts,can significantly reduce the overall cost for the IDC enterprise.展开更多
Background:Research in various academic disciplines has undergone tremendous changes in the era of big data.Everyone is talking about big data nowadays,but how exactly is it being applied in research on financial stud...Background:Research in various academic disciplines has undergone tremendous changes in the era of big data.Everyone is talking about big data nowadays,but how exactly is it being applied in research on financial studies?Results:This study summarizes the sources of Internet big data for research related to capital markets and the analytical methods that have been used in the literature.In addition,it presents a review of the research findings based on Internet big data in the field of capital markets and proposes suggestions for future studies in which big data can be applied to examine issues related to capital markets.Conclusion:(1)Internet big data sources related to present capital market research can be categorized into forum-type data,microblog-type data and search class data.(2)As for research about investors’sentiments on the basis of Internet big data,the main methods of sentiment analysis include building an inventory of lexical categories,using dictionaries for analysis of lexical categories,and machine learning.(3)Many studies address whether Internet big data can predict capital markets.However,they reach no consistent conclusions,which could be due to limitations of sample and analysis method used.(4)Data collection technique and analysis methods require further improvements.展开更多
The industrial Internet of Things(IoT)is a trend of factory development and a basic condition of intelligent factory.It is very important to ensure the security of data transmission in industrial IoT.Applying a new ch...The industrial Internet of Things(IoT)is a trend of factory development and a basic condition of intelligent factory.It is very important to ensure the security of data transmission in industrial IoT.Applying a new chaotic secure communication scheme to address the security problem of data transmission is the main contribution of this paper.The scheme is proposed and studied based on the synchronization of different-structure fractional-order chaotic systems with different order.The Lyapunov stability theory is used to prove the synchronization between the fractional-order drive system and the response system.The encryption and decryption process of the main data signals is implemented by using the n-shift encryption principle.We calculate and analyze the key space of the scheme.Numerical simulations are introduced to show the effectiveness of theoretical approach we proposed.展开更多
This paper explains the basic concepts of " Internet + " and big data,analyzes the main problems in the application of big data technology in agricultural informationization of Shandong Province,summarizes c...This paper explains the basic concepts of " Internet + " and big data,analyzes the main problems in the application of big data technology in agricultural informationization of Shandong Province,summarizes corresponding solutions from the aspects of government guidance,financial input,open sharing of agricultural big data,big data storage and processing,data mining,etc.,and prospects the application trend of big data technology in agricultural informationization to achieve the connotative development of agriculture in Shandong Province.展开更多
Energy Internet is deeply integrated by Internet concept, information technology and energy industry, and Energy Internet Big Data are one of core technologies that achieve energy-information-economic interconnection ...Energy Internet is deeply integrated by Internet concept, information technology and energy industry, and Energy Internet Big Data are one of core technologies that achieve energy-information-economic interconnection and improve the development and evolution of Energy Internet. This paper describes the concept and characteristics of Energy Internet Big Data, and feasibility of applying Energy Internet Big Data to integrated energy market. On this basis, as for integrated energy market and multi-subjects of Energy Internet, typical application and technical system based on Energy Internet Big Data in integrated energy market is put forward, which provides a reference for the analysis and decision of integrated energy market in Energy Internet.展开更多
基金supported in part by the National Natural Science Foundation of China under Grant 52177082in part by the Beijing Nova Program under Grant 20220484007.
文摘With the advent of the digital economy,there has been a rapid proliferation of small-scale Internet data centers(SIDCs).By leveraging their spatiotemporal load regulation potential through data workload balancing,aggregated SIDCs have emerged as promising demand response(DR)resources for future power distribution systems.This paper presents an innovative framework for assessing capacity value(CV)by aggregating SIDCs participating in DR programs(SIDC-DR).Initially,we delineate the concept of CV tailored for aggregated SIDC scenarios and establish a metric for the assessment.Considering the effects of the data load dynamics,equipment constraints,and user behavior,we developed a sophisticated DR model for aggregated SIDCs using a data network aggregation method.Unlike existing studies,the proposed model captures the uncertainties associated with end tenant decisions to opt into an SIDC-DR program by utilizing a novel uncertainty modeling approach called Z-number formulation.This approach accounts for both the uncertainty in user participation intentions and the reliability of basic information during the DR process,enabling high-resolution profiling of the SIDC-DR potential in the CV evaluation.Simulation results from numerical studies conducted on a modified IEEE-33 node distribution system confirmed the effectiveness of the proposed approach and highlighted the potential benefits of SIDC-DR utilization in the efficient operation of future power systems.
基金funded by National Key Research and Development Plan,China(2019YFE0112700)China Postdoctoral Science Foundation(2021M701937)+2 种基金National Science Foundation for Distinguished Young Scholars(52125806)National Natural Science Foundation of China(51908519)Shuimu Tsinghua Scholar Program(2021SM005)。
文摘Internet data center buildings have great importance for maintaining the post-earthquake functionality of telecommunication networks.It is essential to maintain the functionality of internet data center buildings during earthquakes or recover immediately after earthquakes,which is referred to as seismic resilience.In this study,a seismic resilience assessment framework based on the Chinese code GB/T 38591-2020 is introduced first.The seismic damage and post-earthquake repair of both structural components and non-structural components are considered in the resilience assessment framework.A method for post-earthquake functionality loss quantification is proposed based on damage state and functionality loss of component.The subsystem level and system level functionality loss can be obtained by an integration principle.The seismic resilience of a typical internet data center building was evaluated to demonstrate the effectiveness of the proposed method.To enhance the seismic resilience level,different disaster mitigation techniques including the energy dissipation technology using buckling restrained braces and the base-isolation technology using lead-rubber bearings are adopted.The seismic resilience is quantified and the corresponding seismic resilience curves under different earthquake intensities are developed based on evaluation results.
文摘Energy generation and consumption are the main aspects of social life due to the fact that modern people’s necessity for energy is a crucial ingredient for existence. Therefore, energy efficiency is regarded as the best economical approach to provide safer and affordable energy for both utilities and consumers, through the enhancement of energy security and reduction of energy emissions. One of the problems of cloud computing service providers is the high rise in the cost of energy, efficiency together with carbon emission with regards to the running of their internet data centres (IDCs). In order to mitigate these issues, smart micro-grid was found to be suitable in increasing the energy efficiency, sustainability together with the reliability of electrical services for the IDCs. Therefore, this paper presents idea on how smart micro-grids can bring down the disturbing cost of energy, carbon emission by the IDCs with some level of energy efficiency all in an effort to attain green cloud computing services from the service providers. In specific term, we aim at achieving green information and communication technology (ICT) in the field of cloud computing in relations to energy efficiency, cost-effectiveness and carbon emission reduction from cloud data center’s perspective.
基金supported by the National Key Research and Development Program of China(Project No.2023YFC2307500).
文摘Influenza,an acute respiratory infectious disease caused by the influenza virus,exhibits distinct seasonal patterns in China,with peak activity occurring in winter and spring in northern regions,and in winter and summer in southern areas[1].The World Health Organization(WHO)emphasizes that early warning and epidemic intensity assessments are critical public health strategies for influenza prevention and control.Internet-based flu surveillance,with real-time data and low costs,effectively complements traditional methods.The Baidu Search Index,which reflects flu-related queries,strongly correlates with influenza trends,aiding in regional activity assessment and outbreak tracking[2].
基金This work was supported in part by the Support Project by the Ministry of Science and Technology of State Grid Corporation of China under Grant SGBJDK00KJJS1900085the World Bank China Renewable Energy Development Project Management Office.
文摘The development of cloud computing has accel-erated the worldwide growth of internet data centers(IDCs).While a large portion of the energy consumption generated by intense computation introduces greater operation expenditures to the IDC enterprises.To manage the overall costs and utilize resources to their fullest extent,this paper introduces the concept of spatio-temporal workload allocation among the geographically distributed IDCs within a cloud,with the guarantee of the workload completion time and the consideration of computing service delay penalties by introducing the cost of inconvenience.Apart from the effort of the workload migration,the spatio-temporal variance of the renewable energies in the data center microgrids(DMGs)is fully considered in this paper.What's more,as the power consumed by the IDCs are primarily converted into heat,the waste heat recovery process is embedded in each IDC to demonstrate the effectiveness of the repurposed heat,which can be used by the residential heating demand in the thermal system,for total cost reduction and energy usage efficiency in the whole operating system.Applying real-life data traces of the electricity price,renewable energies and heating demand,these extensive evaluations demonstrate that both spatial and temporal complementary attempts on the supply side and demand side,along with power and thermal complementary efforts,can significantly reduce the overall cost for the IDC enterprise.
基金National Nature Sciences Foundation of China(No.71372148).
文摘Background:Research in various academic disciplines has undergone tremendous changes in the era of big data.Everyone is talking about big data nowadays,but how exactly is it being applied in research on financial studies?Results:This study summarizes the sources of Internet big data for research related to capital markets and the analytical methods that have been used in the literature.In addition,it presents a review of the research findings based on Internet big data in the field of capital markets and proposes suggestions for future studies in which big data can be applied to examine issues related to capital markets.Conclusion:(1)Internet big data sources related to present capital market research can be categorized into forum-type data,microblog-type data and search class data.(2)As for research about investors’sentiments on the basis of Internet big data,the main methods of sentiment analysis include building an inventory of lexical categories,using dictionaries for analysis of lexical categories,and machine learning.(3)Many studies address whether Internet big data can predict capital markets.However,they reach no consistent conclusions,which could be due to limitations of sample and analysis method used.(4)Data collection technique and analysis methods require further improvements.
基金supported in part by the National Science Foundation Project of China (61931001, 61873026)the National Key R&D Program of China (2017YFC0820700)
文摘The industrial Internet of Things(IoT)is a trend of factory development and a basic condition of intelligent factory.It is very important to ensure the security of data transmission in industrial IoT.Applying a new chaotic secure communication scheme to address the security problem of data transmission is the main contribution of this paper.The scheme is proposed and studied based on the synchronization of different-structure fractional-order chaotic systems with different order.The Lyapunov stability theory is used to prove the synchronization between the fractional-order drive system and the response system.The encryption and decryption process of the main data signals is implemented by using the n-shift encryption principle.We calculate and analyze the key space of the scheme.Numerical simulations are introduced to show the effectiveness of theoretical approach we proposed.
基金Supported by Science Research Foundation of Binzhou University(BZXYG1712,BZXYG1714)Teaching and Research Project(BZXYSYXM201606,BZXYWTXM201621)Soft Science Research Project of Shandong Province(2018RKB01136)
文摘This paper explains the basic concepts of " Internet + " and big data,analyzes the main problems in the application of big data technology in agricultural informationization of Shandong Province,summarizes corresponding solutions from the aspects of government guidance,financial input,open sharing of agricultural big data,big data storage and processing,data mining,etc.,and prospects the application trend of big data technology in agricultural informationization to achieve the connotative development of agriculture in Shandong Province.
文摘Energy Internet is deeply integrated by Internet concept, information technology and energy industry, and Energy Internet Big Data are one of core technologies that achieve energy-information-economic interconnection and improve the development and evolution of Energy Internet. This paper describes the concept and characteristics of Energy Internet Big Data, and feasibility of applying Energy Internet Big Data to integrated energy market. On this basis, as for integrated energy market and multi-subjects of Energy Internet, typical application and technical system based on Energy Internet Big Data in integrated energy market is put forward, which provides a reference for the analysis and decision of integrated energy market in Energy Internet.
