The neighbor knowledge in mobile ad hoc networks is important information. However, the accuracy of neighbor knowledge is paid in terms of energy consumption. In traditional schemes for neighbor discovery, a mobile no...The neighbor knowledge in mobile ad hoc networks is important information. However, the accuracy of neighbor knowledge is paid in terms of energy consumption. In traditional schemes for neighbor discovery, a mobile node uses fixed period to send HELLO messages to notify its existence. An adaptive scheme was proposed. The objective is that when mobile nodes are distributed sparsely or move slowly, fewer HELLO messages are needed to achieve reasonable accuracy, while in a mutable network where nodes are dense or move quickly, they can adaptively send more HELLO messages to ensure the accuracy. Simulation results show that the adaptive scheme achieves the objective and performs effectively.展开更多
The aim of this work is to investigate the general functional properties of the intracellular governing gene/epigene networks. A body of mathematics used in automata and graphs theories is adequate for revealing the g...The aim of this work is to investigate the general functional properties of the intracellular governing gene/epigene networks. A body of mathematics used in automata and graphs theories is adequate for revealing the general dynamic properties of governing gene and epigene networks and provides a methodic basis for efficient analytical algorithms. The obtained results permit to reveal the properties of the characteristic function （transitions and outputs） of the cellular automata as models for the intracellular governing gene/epigene networks.展开更多
The Deep Packet Inspection(DPI)method is a popular method that can accurately identify the flow data and its corresponding application.Currently,the DPI method is widely used in common network management systems.Howev...The Deep Packet Inspection(DPI)method is a popular method that can accurately identify the flow data and its corresponding application.Currently,the DPI method is widely used in common network management systems.However,the major limitation of DPI systems is that their signature library is mainly extracted manually,which makes it hard to efficiently obtain the signature of new applications.Hence,in this paper,we propose an automatic signature extraction mechanism using Principal Component Analysis(PCA)technology,which is able to extract the signature automatically.In the proposed method,the signatures are expressed in the form of serial consistent sequences constructed by principal components instead of normally separated substrings in the original data extracted from the traditional methods.Extensive experiments based on numerous sets of data have been carried out to evaluate the performance of the proposed scheme,and the results prove that the newly proposed method can achieve good performance in terms of accuracy and efficiency.展开更多
The paper focuses on amalgamation of automata theory and fuzzy language. It uses adaptive knowledge based abstract framework which uses dynamic neural network framework along with fuzzy automata as Models of Learning,...The paper focuses on amalgamation of automata theory and fuzzy language. It uses adaptive knowledge based abstract framework which uses dynamic neural network framework along with fuzzy automata as Models of Learning, combining the two methodologies the authors develop a new framework termed as Fuzzy Automata based Neural Network （FANN）. It highlights conversion of knowledge rule to fuzzy automata thereby generating a framework FANN. FANN consists of composite fuzzy automation divided into ＂Performance Evaluator＂ and ＂Feature Extraction＂ which takes the help of previously stored samples of similar situations. The authors have extended FANN for Urban Traffic Modeling.展开更多
The article is research on the traffic situations of freeways. Different rules make different traffic situations. It is meaningful to research on traffic situations under different conditions. The author analyzes fac...The article is research on the traffic situations of freeways. Different rules make different traffic situations. It is meaningful to research on traffic situations under different conditions. The author analyzes factors like traffic flow and safety, peflbrmance respectively, and proposes the theor3, basis for making more reasonable rules. The author first establishes evaluation system of traffic safety. Then, we compare the freeway network to power network to find a solution. and establish a traffic flow model based on power flow （TFPF）. It calculates power flow. So it applies the formula mode back to the traffic network, chalking up the perforumnce of the traffic condition. We utilize cellular automata （CA） method to simulate traffic circulation, and verify the accuracy of above model with the obtained data.展开更多
基金The National Natural Science Foundation ofChina (No 60575036)The National BasicResearch Program (973) of China (No2002cb312200)
文摘The neighbor knowledge in mobile ad hoc networks is important information. However, the accuracy of neighbor knowledge is paid in terms of energy consumption. In traditional schemes for neighbor discovery, a mobile node uses fixed period to send HELLO messages to notify its existence. An adaptive scheme was proposed. The objective is that when mobile nodes are distributed sparsely or move slowly, fewer HELLO messages are needed to achieve reasonable accuracy, while in a mutable network where nodes are dense or move quickly, they can adaptively send more HELLO messages to ensure the accuracy. Simulation results show that the adaptive scheme achieves the objective and performs effectively.
文摘The aim of this work is to investigate the general functional properties of the intracellular governing gene/epigene networks. A body of mathematics used in automata and graphs theories is adequate for revealing the general dynamic properties of governing gene and epigene networks and provides a methodic basis for efficient analytical algorithms. The obtained results permit to reveal the properties of the characteristic function （transitions and outputs） of the cellular automata as models for the intracellular governing gene/epigene networks.
基金supported by the National Natural Science Foundation of China under Grant No.61003282Beijing Higher Education Young Elite Teacher Project+3 种基金China Next Generation Internet(CNGI)Project"Research and Trial on Evolving Next Generation Network Intelligence Capability Enhancement(NICE)"the National Basic Research Program(973 Program)under Grant No.2009CB320-505the National Science and Technology Major Project"Research about Architecture of Mobile Internet"under Grant No.2011ZX03-002-001-01the National High Technology Research and Development Program(863 Program)under Grant No.2011AA010704
文摘The Deep Packet Inspection(DPI)method is a popular method that can accurately identify the flow data and its corresponding application.Currently,the DPI method is widely used in common network management systems.However,the major limitation of DPI systems is that their signature library is mainly extracted manually,which makes it hard to efficiently obtain the signature of new applications.Hence,in this paper,we propose an automatic signature extraction mechanism using Principal Component Analysis(PCA)technology,which is able to extract the signature automatically.In the proposed method,the signatures are expressed in the form of serial consistent sequences constructed by principal components instead of normally separated substrings in the original data extracted from the traditional methods.Extensive experiments based on numerous sets of data have been carried out to evaluate the performance of the proposed scheme,and the results prove that the newly proposed method can achieve good performance in terms of accuracy and efficiency.
文摘The paper focuses on amalgamation of automata theory and fuzzy language. It uses adaptive knowledge based abstract framework which uses dynamic neural network framework along with fuzzy automata as Models of Learning, combining the two methodologies the authors develop a new framework termed as Fuzzy Automata based Neural Network （FANN）. It highlights conversion of knowledge rule to fuzzy automata thereby generating a framework FANN. FANN consists of composite fuzzy automation divided into ＂Performance Evaluator＂ and ＂Feature Extraction＂ which takes the help of previously stored samples of similar situations. The authors have extended FANN for Urban Traffic Modeling.
文摘The article is research on the traffic situations of freeways. Different rules make different traffic situations. It is meaningful to research on traffic situations under different conditions. The author analyzes factors like traffic flow and safety, peflbrmance respectively, and proposes the theor3, basis for making more reasonable rules. The author first establishes evaluation system of traffic safety. Then, we compare the freeway network to power network to find a solution. and establish a traffic flow model based on power flow （TFPF）. It calculates power flow. So it applies the formula mode back to the traffic network, chalking up the perforumnce of the traffic condition. We utilize cellular automata （CA） method to simulate traffic circulation, and verify the accuracy of above model with the obtained data.
