In-network caching and Interest packets aggregation are two important features of Content-Centric Networking(CCN).CCN routers can directly respond to the Interest request by Content Store(CS)and aggregate the same Int...In-network caching and Interest packets aggregation are two important features of Content-Centric Networking(CCN).CCN routers can directly respond to the Interest request by Content Store(CS)and aggregate the same Interest packets by Pending Interest Table(PIT).In this way,most popular content requests will not reach the origin content server.Thus,content providers will be unaware of the actual usages of their contents in network.This new network paradigm presents content providers with unprecedented challenge.It will bring a great impact on existing mature business model of content providers,such as advertising revenue model based on hits amount.To leverage the advantages of CCN and the realistic business needs of content providers,we explore the hits-based content provisioning mechanism in CCN.The proposed approaches can avoid the unprecedented impact on content providers' existing business model and promote content providers to embrace the real deployment of CCN network.展开更多
Ensuring stable frequency and voltage has recently become increasingly challenging for modern power systems. This is primarily due to the fluctuating and intermittent nature of renewable energy sources and the uncerta...Ensuring stable frequency and voltage has recently become increasingly challenging for modern power systems. This is primarily due to the fluctuating and intermittent nature of renewable energy sources and the uncertain electricity demand. To address these issues, this study proposes a load resource management(LRM) method to cope with the sudden power disturbances. The LRM method supports primary frequency and voltage regulation, and its integration with network dynamics minimizes the established disutility function caused by load participation. For better control performance, a non-dominated sorting genetic algorithm-Ⅱ(NSGA-Ⅱ)-based gain-tuning procedure was utilized for LRM, aiming to enhance the frequency/voltage nadir, reduce the frequency/voltage steady-state error, and minimize the total load control efforts. To validate the effectiveness of the proposed approach, comparative experiments were conducted with three load–resource management technologies for primary regulation auxiliary services in MATLAB/Simulink. Compared to the conventional optimal load control or using LRM alone, the improved NSGA-Ⅱ-based LRM demonstrates superior performance. It achieves better frequency response, voltage transients, and steady-state responses, while also considering disutility.展开更多
随着互联网技术的发展和普及,广播电视流媒体传输已经成为人们获取信息和娱乐的重要方式之一。然而由于网络环境的复杂性和不稳定性,如何保证流媒体传输的质量成一个重要的问题。内容分发网络(Content Distribution Network,CDN)作为一...随着互联网技术的发展和普及,广播电视流媒体传输已经成为人们获取信息和娱乐的重要方式之一。然而由于网络环境的复杂性和不稳定性,如何保证流媒体传输的质量成一个重要的问题。内容分发网络(Content Distribution Network,CDN)作为一种有效的解决方案被广泛应用于流媒体传输。为优化传输质量、提高用户体验,探讨基于CDN的广播电视流媒体传输质量优化方法。展开更多
The primary purpose of the Energy Management Scheme(EMS)is to monitor the energy fluctuations present in the load profile.In this paper,the improved model predictive controller is adopted for the EMS in the power syst...The primary purpose of the Energy Management Scheme(EMS)is to monitor the energy fluctuations present in the load profile.In this paper,the improved model predictive controller is adopted for the EMS in the power system.Emperor Penguin Optimization(EPO)algorithm optimized Artificial Neural Network(ANN)with Model Predictive Control(MPC)scheme for accurate prediction of load and power forecasting at the time of preoptimizing EMS is presented.For the power generation,Renewable Energy Sources(RES)such as photo voltaic(PV)and wind turbine(WT)are utilized along with that the fuel cell is also presented in case of failure by the RES.Such a setup is connected with the grid and applies to the household appliances.In improved model predictive control(IMPC),the set of constraints for the powerflow in the system is optimized by the ANN,which is trained by EPO.Such a tuning based prediction model is presented in the IMPC technique.The proposed work is implemented in the MATLAB/Simulink platform.The energy management capability of the proposed system is analyzed for different atmospheric conditions.The total system cost,life cycle cost and annualized cost for IMPC are 48%,45%and 15%,respectively.From the performance analysis,the cost obtained by the proposed method is very low compared to that obtained by the existing techniques.展开更多
基金This work was supported by National Key Basic Research Program of China （973 Program） under Grant No. 2012CB315802 National Natural Science Foundation of China under Grant No. 61171102 and No. 61132001 Prospective Research on Future Networks of Jiangsu Future Networks Innovation institute under Grant No. BY2013095-4-01. Beijing Nova Program under Grant No.2008B50 and Beijing Higher Education Young Elite Teacher Project under Grant No.YETP0478.
文摘In-network caching and Interest packets aggregation are two important features of Content-Centric Networking(CCN).CCN routers can directly respond to the Interest request by Content Store(CS)and aggregate the same Interest packets by Pending Interest Table(PIT).In this way,most popular content requests will not reach the origin content server.Thus,content providers will be unaware of the actual usages of their contents in network.This new network paradigm presents content providers with unprecedented challenge.It will bring a great impact on existing mature business model of content providers,such as advertising revenue model based on hits amount.To leverage the advantages of CCN and the realistic business needs of content providers,we explore the hits-based content provisioning mechanism in CCN.The proposed approaches can avoid the unprecedented impact on content providers' existing business model and promote content providers to embrace the real deployment of CCN network.
基金support of State Grid Corporation of China Project:Research on key tech-nologies of automatic generation of typical power grid operation modes and automatic calculation of section stability limits(5100-202355420A-3-2-ZN).
文摘Ensuring stable frequency and voltage has recently become increasingly challenging for modern power systems. This is primarily due to the fluctuating and intermittent nature of renewable energy sources and the uncertain electricity demand. To address these issues, this study proposes a load resource management(LRM) method to cope with the sudden power disturbances. The LRM method supports primary frequency and voltage regulation, and its integration with network dynamics minimizes the established disutility function caused by load participation. For better control performance, a non-dominated sorting genetic algorithm-Ⅱ(NSGA-Ⅱ)-based gain-tuning procedure was utilized for LRM, aiming to enhance the frequency/voltage nadir, reduce the frequency/voltage steady-state error, and minimize the total load control efforts. To validate the effectiveness of the proposed approach, comparative experiments were conducted with three load–resource management technologies for primary regulation auxiliary services in MATLAB/Simulink. Compared to the conventional optimal load control or using LRM alone, the improved NSGA-Ⅱ-based LRM demonstrates superior performance. It achieves better frequency response, voltage transients, and steady-state responses, while also considering disutility.
文摘随着互联网技术的发展和普及,广播电视流媒体传输已经成为人们获取信息和娱乐的重要方式之一。然而由于网络环境的复杂性和不稳定性,如何保证流媒体传输的质量成一个重要的问题。内容分发网络(Content Distribution Network,CDN)作为一种有效的解决方案被广泛应用于流媒体传输。为优化传输质量、提高用户体验,探讨基于CDN的广播电视流媒体传输质量优化方法。
文摘The primary purpose of the Energy Management Scheme(EMS)is to monitor the energy fluctuations present in the load profile.In this paper,the improved model predictive controller is adopted for the EMS in the power system.Emperor Penguin Optimization(EPO)algorithm optimized Artificial Neural Network(ANN)with Model Predictive Control(MPC)scheme for accurate prediction of load and power forecasting at the time of preoptimizing EMS is presented.For the power generation,Renewable Energy Sources(RES)such as photo voltaic(PV)and wind turbine(WT)are utilized along with that the fuel cell is also presented in case of failure by the RES.Such a setup is connected with the grid and applies to the household appliances.In improved model predictive control(IMPC),the set of constraints for the powerflow in the system is optimized by the ANN,which is trained by EPO.Such a tuning based prediction model is presented in the IMPC technique.The proposed work is implemented in the MATLAB/Simulink platform.The energy management capability of the proposed system is analyzed for different atmospheric conditions.The total system cost,life cycle cost and annualized cost for IMPC are 48%,45%and 15%,respectively.From the performance analysis,the cost obtained by the proposed method is very low compared to that obtained by the existing techniques.
