A system designed for supporting the network performance analysis and forecast effort is presented, based on the combination of offline network analysis and online real-time performance forecast. The off-line analysis...A system designed for supporting the network performance analysis and forecast effort is presented, based on the combination of offline network analysis and online real-time performance forecast. The off-line analysis will perform analysis of specific network node performance, correlation analysis of relative network nodes performance and evolutionary mathematical modeling of long-term network performance measurements. The online real-time network performance forecast will be based on one so-called hybrid prediction modeling approach for short-term network, performance prediction and trend analysis. Based on the module design, the system proposed has good intelligence, scalability and self-adaptability, which will offer highly effective network performance analysis and forecast tools for network managers, and is one ideal support platform for network performance analysis and forecast effort.展开更多
Emulation platforms are critical for evaluation and verification in the research of networking technologies and protocols for space networks(SN).High fidelity emulating technologies have been extensively studied for S...Emulation platforms are critical for evaluation and verification in the research of networking technologies and protocols for space networks(SN).High fidelity emulating technologies have been extensively studied for SN in earlier work,while little emphasis has been placed on the performance evaluation part.In this paper,the design of a network performance analysis architecture is presented,with which high-speed network traffic can be captured and indexed,and the performance of the emulated SN can be well analyzed and evaluated.This architecture comprises three components,namely capture layer,storage layer and analysis layer.Analytic Hierarchy Process(AHP)and several analysis methods are adopted to evaluate the network performance comprehensively.In the implementation of the proposed architecture,configuration optimization and parallel processing are applied to handle large amount of high-speed network traffic.Finally,experiment results through the analysis system exhibits the effectiveness of the proposed architecture.展开更多
The phenomenon of data explosion represents a severe challenge for the upcoming big data era.However,the current Internet architecture is insufficient for dealing with a huge amount of traffic owing to an increase in ...The phenomenon of data explosion represents a severe challenge for the upcoming big data era.However,the current Internet architecture is insufficient for dealing with a huge amount of traffic owing to an increase in redundant content transmission and the end-point-based communication model.Information-centric networking(ICN)is a paradigm for the future Internet that can be utilized to resolve the data explosion problem.In this paper,we focus on content-centric networking(CCN),one of the key candidate ICN architectures.CCN has been studied in various network environments with the aim of relieving network and server burden,especially in name-based forwarding and in-network caching functionalities.This paper studies the effect of several caching strategies in the CCN domain from the perspective of network and server overhead.Thus,we comprehensively analyze the in-network caching performance of CCN under several popular cache replication methods(i.e.,cache placement).We evaluate the performance with respect to wellknown Internet traffic patterns that follow certain probabilistic distributions,such as the Zipf/Mandelbrot–Zipf distributions,and flashcrowds.For the experiments,we developed an OPNET-based CCN simulator with a realistic Internet-like topology.展开更多
基金the National 863 High-Tech Project (863 -3 0 0 -0 2 -0 9-99) and Key Research Project of Hubei Province(991P110 )
文摘A system designed for supporting the network performance analysis and forecast effort is presented, based on the combination of offline network analysis and online real-time performance forecast. The off-line analysis will perform analysis of specific network node performance, correlation analysis of relative network nodes performance and evolutionary mathematical modeling of long-term network performance measurements. The online real-time network performance forecast will be based on one so-called hybrid prediction modeling approach for short-term network, performance prediction and trend analysis. Based on the module design, the system proposed has good intelligence, scalability and self-adaptability, which will offer highly effective network performance analysis and forecast tools for network managers, and is one ideal support platform for network performance analysis and forecast effort.
基金supported by the National Natural Science Foundation of China under Grant 62131012the Fundamental Research Funds for the Central Universities under Grant 021014380187。
文摘Emulation platforms are critical for evaluation and verification in the research of networking technologies and protocols for space networks(SN).High fidelity emulating technologies have been extensively studied for SN in earlier work,while little emphasis has been placed on the performance evaluation part.In this paper,the design of a network performance analysis architecture is presented,with which high-speed network traffic can be captured and indexed,and the performance of the emulated SN can be well analyzed and evaluated.This architecture comprises three components,namely capture layer,storage layer and analysis layer.Analytic Hierarchy Process(AHP)and several analysis methods are adopted to evaluate the network performance comprehensively.In the implementation of the proposed architecture,configuration optimization and parallel processing are applied to handle large amount of high-speed network traffic.Finally,experiment results through the analysis system exhibits the effectiveness of the proposed architecture.
基金supported by Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(2014R1A1A2057796)and(2015R1D1A1A01059049)
文摘The phenomenon of data explosion represents a severe challenge for the upcoming big data era.However,the current Internet architecture is insufficient for dealing with a huge amount of traffic owing to an increase in redundant content transmission and the end-point-based communication model.Information-centric networking(ICN)is a paradigm for the future Internet that can be utilized to resolve the data explosion problem.In this paper,we focus on content-centric networking(CCN),one of the key candidate ICN architectures.CCN has been studied in various network environments with the aim of relieving network and server burden,especially in name-based forwarding and in-network caching functionalities.This paper studies the effect of several caching strategies in the CCN domain from the perspective of network and server overhead.Thus,we comprehensively analyze the in-network caching performance of CCN under several popular cache replication methods(i.e.,cache placement).We evaluate the performance with respect to wellknown Internet traffic patterns that follow certain probabilistic distributions,such as the Zipf/Mandelbrot–Zipf distributions,and flashcrowds.For the experiments,we developed an OPNET-based CCN simulator with a realistic Internet-like topology.
