The increasing network throughput challenges the current network traffic monitor systems to have compatible high-performance data processing.The design of packet processing systems is guided by the requirements of hig...The increasing network throughput challenges the current network traffic monitor systems to have compatible high-performance data processing.The design of packet processing systems is guided by the requirements of high packet processing throughput.In this paper,we depict an in-depth research on the related techniques and an implementation of a high-performance data acquisition mechanism.Through the bottleneck analysis with the aid of queuing network model,several performance optimising methods,such as service rate increasing,queue removing and model simplification,are integrated.The experiment results indicate that this approach is capable of reducing the CPU utilization ratio while improving the efficiency of data acquisition in high-speed networks.展开更多
The hydrophobic-polar (HP) lattice model is an important simplified model for studying protein folding. In this paper, we present an improved ACO algorithm for the protein structure prediction. In the algorithm, the &...The hydrophobic-polar (HP) lattice model is an important simplified model for studying protein folding. In this paper, we present an improved ACO algorithm for the protein structure prediction. In the algorithm, the "lone"ethod is applied to deal with the infeasible structures, and the "oint mutation and reconstruction"ethod is applied in local search phase. The empirical results show that the presented method is feasible and effective to solve the problem of protein structure prediction, and notable improvements in CPU time are obtained.展开更多
基金ACKNOWLEDGEMENT This project was supported by the National Natural Science Foundation of China under Grant No. 61170262 the National High Tech- nology Research and Development Program of China （863 Program） under Grants No. 2012AA012506, No. 2012AA012901, No. 2012- AA012903+5 种基金 the Specialised Research Fund for the Doctoral Program of Higher Education of China under Grant No. 20121103120032 the Humanity and Social Science Youth Founda- tion of Ministry of Education of China under Grant No. 13YJCZH065 the Opening Project of Key Lab of Information Network Security of Ministry of Public Security （The Third Re- search Institute of Ministry of Public Security） under Grant No. C13613 the China Postdoc- toral Science Foundation, General Program of Science and Technology Development Project of Beijing Municipal Education Commission of China under Grant No. km201410005012 the Research on Education and Teaching of Beijing University of Technology under Grant No. ER2013C24 the Beijing Municipal Natu- ral Science Foundation, Sponsored by Hunan Postdoctoral Scientific Program, Open Re- search Fund of Beijing Key Laboratory of Trusted Computing.
文摘The increasing network throughput challenges the current network traffic monitor systems to have compatible high-performance data processing.The design of packet processing systems is guided by the requirements of high packet processing throughput.In this paper,we depict an in-depth research on the related techniques and an implementation of a high-performance data acquisition mechanism.Through the bottleneck analysis with the aid of queuing network model,several performance optimising methods,such as service rate increasing,queue removing and model simplification,are integrated.The experiment results indicate that this approach is capable of reducing the CPU utilization ratio while improving the efficiency of data acquisition in high-speed networks.
文摘The hydrophobic-polar (HP) lattice model is an important simplified model for studying protein folding. In this paper, we present an improved ACO algorithm for the protein structure prediction. In the algorithm, the "lone"ethod is applied to deal with the infeasible structures, and the "oint mutation and reconstruction"ethod is applied in local search phase. The empirical results show that the presented method is feasible and effective to solve the problem of protein structure prediction, and notable improvements in CPU time are obtained.
