Active Queue Management (AQM) is an active research area in the Internet community. Random Early Detection (RED) is a typical AQM algorithm, but it is known that it is difficult to configure its parameters and its ave...Active Queue Management (AQM) is an active research area in the Internet community. Random Early Detection (RED) is a typical AQM algorithm, but it is known that it is difficult to configure its parameters and its average queue length is closely related to the load level. This paper proposes an effective fuzzy congestion control algorithm based on fuzzy logic which uses the pre- dominance of fuzzy logic to deal with uncertain events. The main advantage of this new congestion control algorithm is that it discards the packet dropping mechanism of RED, and calculates packet loss according to a preconfigured fuzzy logic by using the queue length and the buffer usage ratio. Theo- retical analysis and Network Simulator (NS) simulation results show that the proposed algorithm achieves more throughput and more stable queue length than traditional schemes. It really improves a router's ability in network congestion control in IP network.展开更多
Internet traffic classification is vital to the areas of network operation and management. Traditionalclassification methods such as port mapping and payload analysis are becoming increasingly difficult asnewly emerge...Internet traffic classification is vital to the areas of network operation and management. Traditionalclassification methods such as port mapping and payload analysis are becoming increasingly difficult asnewly emerged applications (e.g. Peer-to-Peer) using dynamic port numbers, masquerading techniquesand encryption to avoid detection. This paper presents a machine learning (ML) based traffic classificationscheme, which offers solutions to a variety of network activities and provides a platform of performanceevaluation for the classifiers. The impact of dataset size, feature selection, number of applicationtypes and ML algorithm selection on classification performance is analyzed and demonstrated by the followingexperiments: (1) The genetic algorithm based feature selection can dramatically reduce the costwithout diminishing classification accuracy. (2) The chosen ML algorithms can achieve high classificationaccuracy. Particularly, REPTree and C4.5 outperform the other ML algorithms when computational complexityand accuracy are both taken into account. (3) Larger dataset and fewer application types wouldresult in better classification accuracy. Finally, early detection with only several initial packets is proposedfor real-time network activity and it is proved to be feasible according to the preliminary results.展开更多
In this letter, we present a novel approach of valve stiction detection using wavelet technology. A new non-invasive method is developed with the closed-loop normal operating data. The redundant dyadic discrete wavele...In this letter, we present a novel approach of valve stiction detection using wavelet technology. A new non-invasive method is developed with the closed-loop normal operating data. The redundant dyadic discrete wavelet transform is used to decompose the data at different resolution scales. Based on the Lipschitz regularity theory, wavelet coefficients analysis across scales is performed to detect the jumps in the controlled variables. Adaptive wavelet de-noising is then applied to the data. Features of the valve stiction patterns are extracted from the de-noised data and the valve stiction probability is calculated.展开更多
The trustworthiness and security of routing in the existing Peer-to-Peer (P2P) networks can not be ensured because of the diversity of the strategies of P2P nodes. This paper firstly uses game theory to establish game...The trustworthiness and security of routing in the existing Peer-to-Peer (P2P) networks can not be ensured because of the diversity of the strategies of P2P nodes. This paper firstly uses game theory to establish game model of the strategies and profits of various types of routing nodes. Then,two incentive mechanisms for the corresponding stages of P2P trustworthy routing are proposed,namely trust associated mechanism and trust compensated mechanism. Simulation results show that the incentive mechanisms proposed in this paper will encourage cooperation actions of good nodes and restrain malicious actions of bad nodes,which ensure the trustworthiness of routing consequently.展开更多
The limits of parameter γ in FAST TCP are studied in this paper. A continuous time fluid flow model of the link buffer is considered to create a linear control system related to FAST TCP. Linearing the fluid flow mod...The limits of parameter γ in FAST TCP are studied in this paper. A continuous time fluid flow model of the link buffer is considered to create a linear control system related to FAST TCP. Linearing the fluid flow model and window control model, the Laplace transform version of congestion control system are presented. It results in a negative feedback system with open loop transfer function. With the analysis of Nyquist curve of the system, a sufficient condition on asymptotical stability of FAST TCP congestion window related to the parameter γ is obtained. Packet level ns-2 simulations are used to verify the theoretical claims.展开更多
Accurate and real-time classification of network traffic is significant to network operation and management such as QoS differentiation, traffic shaping and security surveillance. However, with many newly emerged P2P ...Accurate and real-time classification of network traffic is significant to network operation and management such as QoS differentiation, traffic shaping and security surveillance. However, with many newly emerged P2P applications using dynamic port numbers, masquerading techniques, and payload encryption to avoid detection, traditional classification approaches turn to be ineffective. In this paper, we present a layered hybrid system to classify current Internet traffic, motivated by variety of network activities and their requirements of traffic classification. The proposed method could achieve fast and accurate traffic classification with low overheads and robustness to accommodate both known and unknown/encrypted applications. Furthermore, it is feasible to be used in the context of real-time traffic classification. Our experimental results show the distinct advantages of the proposed classifi- cation system, compared with the one-step Machine Learning (ML) approach.展开更多
in this poper, the delay cia computer communication network as the average end-to-end delay ofpackets in the network is studied. The problem of computing the minimum delay and flow assignment of acomputer network is a...in this poper, the delay cia computer communication network as the average end-to-end delay ofpackets in the network is studied. The problem of computing the minimum delay and flow assignment of acomputer network is a coinbinatorial-optimization one. Further analyses show that it can approximate to a quadratic programing problem. To solve the problem, a new network model featuring global con vergence is used. The simulation results demonstrate the new method is feasible and effective.展开更多
基金Supported by the National High Technology Research and Development of China (863 Program) (No.2003AA121560)the High Technology Research and Development Program of Jiangsu Province (No.BEG2003001).
文摘Active Queue Management (AQM) is an active research area in the Internet community. Random Early Detection (RED) is a typical AQM algorithm, but it is known that it is difficult to configure its parameters and its average queue length is closely related to the load level. This paper proposes an effective fuzzy congestion control algorithm based on fuzzy logic which uses the pre- dominance of fuzzy logic to deal with uncertain events. The main advantage of this new congestion control algorithm is that it discards the packet dropping mechanism of RED, and calculates packet loss according to a preconfigured fuzzy logic by using the queue length and the buffer usage ratio. Theo- retical analysis and Network Simulator (NS) simulation results show that the proposed algorithm achieves more throughput and more stable queue length than traditional schemes. It really improves a router's ability in network congestion control in IP network.
基金Supported by the National High Technology Research and Development Programme of China (No. 2005AA121620, 2006AA01Z232)the Zhejiang Provincial Natural Science Foundation of China (No. Y1080935 )the Research Innovation Program for Graduate Students in Jiangsu Province (No. CX07B_ 110zF)
文摘Internet traffic classification is vital to the areas of network operation and management. Traditionalclassification methods such as port mapping and payload analysis are becoming increasingly difficult asnewly emerged applications (e.g. Peer-to-Peer) using dynamic port numbers, masquerading techniquesand encryption to avoid detection. This paper presents a machine learning (ML) based traffic classificationscheme, which offers solutions to a variety of network activities and provides a platform of performanceevaluation for the classifiers. The impact of dataset size, feature selection, number of applicationtypes and ML algorithm selection on classification performance is analyzed and demonstrated by the followingexperiments: (1) The genetic algorithm based feature selection can dramatically reduce the costwithout diminishing classification accuracy. (2) The chosen ML algorithms can achieve high classificationaccuracy. Particularly, REPTree and C4.5 outperform the other ML algorithms when computational complexityand accuracy are both taken into account. (3) Larger dataset and fewer application types wouldresult in better classification accuracy. Finally, early detection with only several initial packets is proposedfor real-time network activity and it is proved to be feasible according to the preliminary results.
基金Supported by the National High-Tech Research and De-velopment Plan (863) of China (No.2006AA01Z232, No.2009AA01Z212, No.200901Z202)the Natural Science Foundation of Jiangsu Province (No. BK2007603)+2 种基金High-Tech Research Plan of Jiangsu Province (No.BG2007045)Research Climbing Project of NJUPT (No.NY2007044)Foundation of Nanjing University of Information Science and Technology(No.20070025)
文摘In this letter, we present a novel approach of valve stiction detection using wavelet technology. A new non-invasive method is developed with the closed-loop normal operating data. The redundant dyadic discrete wavelet transform is used to decompose the data at different resolution scales. Based on the Lipschitz regularity theory, wavelet coefficients analysis across scales is performed to detect the jumps in the controlled variables. Adaptive wavelet de-noising is then applied to the data. Features of the valve stiction patterns are extracted from the de-noised data and the valve stiction probability is calculated.
基金Supported by the Hi-Tech R&D Program (863) of China (2006AA01Z232)the Research Innovation Program for Graduate Student in Jiangsu Province (CX07B-11OZ)
文摘The trustworthiness and security of routing in the existing Peer-to-Peer (P2P) networks can not be ensured because of the diversity of the strategies of P2P nodes. This paper firstly uses game theory to establish game model of the strategies and profits of various types of routing nodes. Then,two incentive mechanisms for the corresponding stages of P2P trustworthy routing are proposed,namely trust associated mechanism and trust compensated mechanism. Simulation results show that the incentive mechanisms proposed in this paper will encourage cooperation actions of good nodes and restrain malicious actions of bad nodes,which ensure the trustworthiness of routing consequently.
基金Supported by National High-Tech Research and Development Plan (863) of China (No. 2006AA01Z232, No.2009AA01Z212, No. 200901Z202)Natural Science Foundation of Jiangsu Province (No. BK2007603)High-Tech Research Plan of Jiangsu Province (No.BG2007045)
文摘The limits of parameter γ in FAST TCP are studied in this paper. A continuous time fluid flow model of the link buffer is considered to create a linear control system related to FAST TCP. Linearing the fluid flow model and window control model, the Laplace transform version of congestion control system are presented. It results in a negative feedback system with open loop transfer function. With the analysis of Nyquist curve of the system, a sufficient condition on asymptotical stability of FAST TCP congestion window related to the parameter γ is obtained. Packet level ns-2 simulations are used to verify the theoretical claims.
基金Supported in part by the National 863 Project of China (No.2006AA01Z232)Zhejiang Natural Science Founda-tion (No.Y1080935)Research Innovation Program Project for Graduate Students in Jiangsu Province ( No.CX07B_110zF)
文摘Accurate and real-time classification of network traffic is significant to network operation and management such as QoS differentiation, traffic shaping and security surveillance. However, with many newly emerged P2P applications using dynamic port numbers, masquerading techniques, and payload encryption to avoid detection, traditional classification approaches turn to be ineffective. In this paper, we present a layered hybrid system to classify current Internet traffic, motivated by variety of network activities and their requirements of traffic classification. The proposed method could achieve fast and accurate traffic classification with low overheads and robustness to accommodate both known and unknown/encrypted applications. Furthermore, it is feasible to be used in the context of real-time traffic classification. Our experimental results show the distinct advantages of the proposed classifi- cation system, compared with the one-step Machine Learning (ML) approach.
文摘in this poper, the delay cia computer communication network as the average end-to-end delay ofpackets in the network is studied. The problem of computing the minimum delay and flow assignment of acomputer network is a coinbinatorial-optimization one. Further analyses show that it can approximate to a quadratic programing problem. To solve the problem, a new network model featuring global con vergence is used. The simulation results demonstrate the new method is feasible and effective.
