This paper presents not only practical but also instructive mathematical models to simulate tree network formation using the Poisson equation and the Finite Difference Method (FDM). Then, the implications for entropic...This paper presents not only practical but also instructive mathematical models to simulate tree network formation using the Poisson equation and the Finite Difference Method (FDM). Then, the implications for entropic theories are discussed from the viewpoint of Maximum Entropy Production (MEP). According to the MEP principle, open systems existing in the state far from equilibrium are stabilized when entropy production is maximized, creating dissipative structures with low entropy such as the tree-shaped network. We prepare two simulation models: one is the Poisson equation model that simulates the state far from equilibrium, and the other is the Laplace equation model that simulates the isolated state or the state near thermodynamic equilibrium. The output of these equations is considered to be positively correlated to entropy production of the system. Setting the Poisson equation model so that entropy production is maximized, tree network formation is advanced. We suppose that this is due to the invocation of the MEP principle, that is, entropy of the system is lowered by emitting maximal entropy out of the system. On the other hand, tree network formation is not observed in the Laplace equation model. Our simulation results will offer the persuasive evidence that certifies the effect of the MEP principle.展开更多
The nestedness property has become an increasingly important means for devising efficient algorithms for network location problems.There have been attempts to explore the nestedness property of network location proble...The nestedness property has become an increasingly important means for devising efficient algorithms for network location problems.There have been attempts to explore the nestedness property of network location problems with some special cases of the convex ordered median objectives.However,there is little research on the nestedness property for those problems with the concave ordered median objectives.This paper constructs a tree network T and shows that the nestedness property cannot hold for the concave ordered median problem,which fills a gap in the research on the nestedness property.Finally,the authors pose an open problem on identifying the nestedness property for the continuous strategic ordered median problem.展开更多
The sensor virus is a serious threat,as an attacker can simply send a single packet to compromise the entire sensor network.Epidemics become drastic with link additions among sensors when the small world phenomena occ...The sensor virus is a serious threat,as an attacker can simply send a single packet to compromise the entire sensor network.Epidemics become drastic with link additions among sensors when the small world phenomena occur.Two immunization strategies,uniform immunization and temporary immunization,are conducted on small worlds of tree-based wireless sensor networks to combat the sensor viruses.With the former strategy,the infection extends exponentially,although the immunization effectively reduces the contagion speed.With the latter strategy,recurrent contagion oscillations occur in the small world when the spatial-temporal dynamics of the epidemic are considered.The oscillations come from the small-world structure and the temporary immunization.Mathematical analyses on the small world of the Cayley tree are presented to reveal the epidemic dynamics with the two immunization strategies.展开更多
Several data mining techniques such as Hidden Markov Model (HMM), artificial neural network, statistical techniques and expert systems are used to model network packets in the field of intrusion detection. In this pap...Several data mining techniques such as Hidden Markov Model (HMM), artificial neural network, statistical techniques and expert systems are used to model network packets in the field of intrusion detection. In this paper a novel intrusion detection mode based on understandable Neural Network Tree (NNTree) is pre-sented. NNTree is a modular neural network with the overall structure being a Decision Tree (DT), and each non-terminal node being an Expert Neural Network (ENN). One crucial advantage of using NNTrees is that they keep the non-symbolic model ENN’s capability of learning in changing environments. Another potential advantage of using NNTrees is that they are actually “gray boxes” as they can be interpreted easily if the num-ber of inputs for each ENN is limited. We showed through experiments that the trained NNTree achieved a simple ENN at each non-terminal node as well as a satisfying recognition rate of the network packets dataset. We also compared the performance with that of a three-layer backpropagation neural network. Experimental results indicated that the NNTree based intrusion detection model achieved better performance than the neural network based intrusion detection model.展开更多
Fetal distress is one of the main factors to cesarean section in obstetrics and gynecology. If the fetus lack of oxygen in uterus, threat to the fetal health and fetal death could happen. Cardiotocography (CTG) is the...Fetal distress is one of the main factors to cesarean section in obstetrics and gynecology. If the fetus lack of oxygen in uterus, threat to the fetal health and fetal death could happen. Cardiotocography (CTG) is the most widely used technique to monitor the fetal health and fetal heart rate (FHR) is an important index to identify occurs of fetal distress. This study is to propose discriminant analysis (DA), decision tree (DT), and artificial neural network (ANN) to evaluate fetal distress. The results show that the accuracies of DA, DT and ANN are 82.1%, 86.36% and 97.78%, respectively.展开更多
This paper describes a simple method of generating concentration gradients with linear and parabolic profiles by using a Christmas tree-shaped microfluidic network.The microfluidic gradient generator consists of two p...This paper describes a simple method of generating concentration gradients with linear and parabolic profiles by using a Christmas tree-shaped microfluidic network.The microfluidic gradient generator consists of two parts：a Christmas tree-shaped network for gradient generation and a broad microchannel for detection.A two-dimensional model was built to analyze the flow field and the mass transfer in the microfluidic network.The simulating results show that a series of linear and parabolic gradient profiles were generated via adjusting relative flow rate ratios of the two source solutions（R_L^2≥0.995 and _PR^2≥0.999）,which could match well with the experimental results（R_L^2≥0.987 and _PR^2≥0.996）.The proposed method is promising for the generation of linear and parabolic concentration gradient profiles,with the potential in chemical and biological applications such as combinatorial chemistry synthesis,stem cell differentiation or cytotoxicity assays.展开更多
To build any spatial soil database, a set of environmental data including digital elevation model(DEM) and satellite images beside geomorphic landscape description are essentials. Such a database, integrates field obs...To build any spatial soil database, a set of environmental data including digital elevation model(DEM) and satellite images beside geomorphic landscape description are essentials. Such a database, integrates field observations and laboratory analyses data with the results obtained from qualitative and quantitative models. So far, various techniques have been developed for soil data processing. The performance of Artificial Neural Network(ANN) and Decision Tree(DT) models was compared to map out some soil attributes in Alborz Province, Iran. Terrain attributes derived from a DEM along with Landsat 8 ETM+, geomorphology map, and the routine laboratory analyses of the studied area were used as input data. The relationships between soil properties(including sand, silt, clay, electrical conductivity, organic carbon, and carbonates) and the environmental variables were assessed using the Pearson Correlation Coefficient and Principle Components Analysis. Slope, elevation, geomforms, carbonate index, stream network, wetness index, and the band’s number 2, 3, 4, and 5 were the most significantly correlated variables. ANN and DT did not show the same accuracy in predicting all parameters. The DT model showed higher performances in estimating sand(R^2=0.73), silt(R^2=0.70), clay(R^2=0.72), organic carbon(R^2=0.71), and carbonates(R^2=0.70). While the ANN model only showed higher performance in predicting soil electrical conductivity(R^2=0.95). The results showed that determination the best model to use, is dependent upon the relation between the considered soil properties with the environmental variables. However, the DT model showed more reasonable results than the ANN model in this study. The results showed that before using a certain model to predict variability of all soil parameters, it would be better to evaluate the efficiency of all possible models for choosing the best fitted model for each property. In other words, most of the developed models are sitespecific and may not be applicable to use for predicting other soil properties or other area.展开更多
The Wireless Sensor Network (WSN) is spatially distributed autonomous sensor to sense special task. WSN like ZigBee network forms simple interconnecting, low power, and low processing capability wireless devices. The ...The Wireless Sensor Network (WSN) is spatially distributed autonomous sensor to sense special task. WSN like ZigBee network forms simple interconnecting, low power, and low processing capability wireless devices. The ZigBee devices facilitate numerous applications such as pervasive computing, security monitoring and control. ZigBee end devices collect sensing data and send them to ZigBee Coordinator. The Coordinator processes end device requests. The effect of a large number of random unsynchronized requests may degrade the overall network performance. An effective technique is particularly needed for synchronizing available node’s request processing to design a reliable ZigBee network. In this paper, region based priority mechanism is implemented to synchronize request with Tree Routing Method. Riverbed is used to simulate and analyze overall ZigBee network performance. The results show that the performance of the overall priority based ZigBee network model is better than without a priority based model. This research paves the way for further designing and modeling a large scale ZigBee network.展开更多
In a sensor network with a large number of densely populated sensor nodes, a single target of interest may be detected by multiple sensor nodes simultaneously. Data collected from the sensor nodes are usually highly c...In a sensor network with a large number of densely populated sensor nodes, a single target of interest may be detected by multiple sensor nodes simultaneously. Data collected from the sensor nodes are usually highly correlated, and hence energy saving using in-network data fusion becomes possible. A traditional data fusion scheme starts with dividing the network into clusters, followed by electing a sensor node as cluster head in each cluster. A cluster head is responsible for collecting data from all its cluster members, performing data fusion on these data and transmitting the fused data to the base station. Assuming that a sensor node is only capable of handling a single node-to-node transmission at a time and each transmission takes T time-slots, a cluster head with n cluster members will take at least nT time-slots to collect data from all its cluster members. In this paper, a tree-based network structure and its formation algorithms are proposed. Simulation results show that the proposed network structure can greatly reduce the delay in data collection.展开更多
A new core-based shared tree algorithm, viz core-cluster combination-based shared tree （CCST） algorithm and the weighted version （i.e. w-CCST algorithm） are proposed in order to resolve the channel resources waste...A new core-based shared tree algorithm, viz core-cluster combination-based shared tree （CCST） algorithm and the weighted version （i.e. w-CCST algorithm） are proposed in order to resolve the channel resources waste problem in typical source-based multicast routing algorithms in low earth orbit （LEO） satellite IP networks. The CCST algorithm includes the dynamic approximate center （DAC） core selection method and the core-cluster combination multicast route construction scheme. Without complicated onboard computation, the DAC method is uniquely developed for highly dynamic networks of periodical and regular movement. The core-cluster combination method takes core node as the initial core-cluster, and expands it stepwise to construct an entire multicast tree at the lowest tree cost by a shortest path scheme between the newly-generated core-cluster and surplus group members, which results in great bandwidth utilization. Moreover, the w-CCST algorithm is able to strike a balance between performance of tree cost and that of end-to-end propagation delay by adjusting the weighted factor to meet strict end-to-end delay requirements of some real-time multicast services at the expense of a slight increase in tree cost. Finally, performance comparison is conducted between the proposed algorithms and typical algorithms in LEO satellite IP networks. Simulation results show that the CCST algorithm significantly decreases the average tree cost against to the others, and also the average end-to-end propagation delay ofw-CCST algorithm is lower than that of the CCST algorithm.展开更多
The learning Bayesian network （BN） structure from data is an NP-hard problem and still one of the most exciting chal- lenges in the machine learning. In this work, a novel algorithm is presented which combines ideas...The learning Bayesian network （BN） structure from data is an NP-hard problem and still one of the most exciting chal- lenges in the machine learning. In this work, a novel algorithm is presented which combines ideas from local learning, constraint- based, and search-and-score techniques in a principled and ef- fective way. It first reconstructs the junction tree of a BN and then performs a K2-scoring greedy search to orientate the local edges in the cliques of junction tree. Theoretical and experimental results show the proposed algorithm is capable of handling networks with a large number of variables. Its comparison with the well-known K2 algorithm is also presented.展开更多
Asymmetric tree-like branched networks are explored by geometric algorithms. Based on the network, an analysis of the thermal conductivity is presented. The relationship between effective thermal conductivity and geom...Asymmetric tree-like branched networks are explored by geometric algorithms. Based on the network, an analysis of the thermal conductivity is presented. The relationship between effective thermal conductivity and geometric structures is obtained by using the thermal-electrical analogy technique. In all studied cases, a clear behaviour is observed, where angle （δ,θ） among parent branching extended lines, branches and parameter of the geometric structures have stronger effects on the effective thermal conductivity. When the angle δ is fixed, the optical diameter ratio β＋ is dependent on angle θ. Moreover, γand m are not related to β＊. The longer the branch is, the smaller the effective thermal conductivity will be. It is also found that when the angle θ〈δ2, the higher the iteration m is, the lower the thermal conductivity will be and it tends to zero, otherwise, it is bigger than zero. When the diameter ratio β1 〈 0.707 and angle δ is bigger, the optimal k of the perfect ratio increases with the increase of the angle δ; when β1 〉 0.707, the optimal k decreases. In addition, the effective thermal conductivity is always less than that of single channel material. The present results also show that the effective thermal conductivity of the asymmetric tree-like branched networks does not obey Murray＇s law.展开更多
In this work, a hardware intrusion detection system （IDS） model and its implementation are introduced to perform online real-time traffic monitoring and analysis. The introduced system gathers some advantages of man...In this work, a hardware intrusion detection system （IDS） model and its implementation are introduced to perform online real-time traffic monitoring and analysis. The introduced system gathers some advantages of many IDSs： hardware based from implementation point of view, network based from system type point of view, and anomaly detection from detection approach point of view. In addition, it can detect most of network attacks, such as denial of services （DOS）, leakage, etc. from detection behavior point of view and can detect both internal and external intruders from intruder type point of view. Gathering these features in one IDS system gives lots of strengths and advantages of the work. The system is implemented by using field programmable gate array （FPGA）, giving a more advantages to the system. A C5.0 decision tree classifier is used as inference engine to the system and gives a high detection ratio of 99.93%.展开更多
Network security equipment is crucial to information systems, and a proper evaluation model can ensure the quality of network security equipment. However, there is only a few models of comprehensive models nowadays. A...Network security equipment is crucial to information systems, and a proper evaluation model can ensure the quality of network security equipment. However, there is only a few models of comprehensive models nowadays. An index system for network security equipment was established and a model based on attack tree with risk fusion was proposed to obtain the score of qualitative indices. The proposed model implements attack tree model and controlled interval and memory(CIM) model to solve the problem of quantifying qualitative indices, and thus improves the accuracy of the evaluation.展开更多
Tree ring dating plays an important role in obtaining past climate information.The fundamental study of obtaining tree ring samples in typical climate regions is particularly essential.The optimum distribution of tree...Tree ring dating plays an important role in obtaining past climate information.The fundamental study of obtaining tree ring samples in typical climate regions is particularly essential.The optimum distribution of tree ring sampling sites based on climate information from the Climate Observation Network(ORPOM model) is presented in this article.In this setup,the tree rings in a typical region are used for surface representation,by applying excellent correlation with the climate information as the main principle.Taking the Horqin Sandy Land in the cold and arid region of China as an example,the optimum distribution range of the tree ring sampling sites was obtained through the application of the ORPOM model,which is considered a reasonably practical scheme.展开更多
A finite random graph generated by continuous time birth and death processes with exponentially distributed waiting times was investigated, which is similar to a communication network in daily life. The vertices are t...A finite random graph generated by continuous time birth and death processes with exponentially distributed waiting times was investigated, which is similar to a communication network in daily life. The vertices are the living particles, and directed edges go from mothers to daughters. The size of the communication network was studied. Furthermore, the probability of successfully connecting senders with receivers and the transmitting speed of information were obtained.展开更多
In living cells, proteins are dynamically connec ted through biochemical reactions, so its functi onal features are properly encoded into protein protein interaction networks (PINs). Up to pres ent, many efforts have ...In living cells, proteins are dynamically connec ted through biochemical reactions, so its functi onal features are properly encoded into protein protein interaction networks (PINs). Up to pres ent, many efforts have been devoted to exploring the basic feature of PINs. However, it is still a challenging problem to explore a universal pr operty of PINs. Here we employed the complex networks theory to analyze the proteinprotein interactions from Database of Interacting Prot ein. Complex tree: the unique framework of PINs was revealed by three topological properties of the giant component of PINs (GCOP), including rightskewed degree distributions, relatively sm all clustering coefficients and short characteristic path lengths. Furthermore, we proposed a no nlinearly growth model: complex tree model to reflect the tree framework, the simulation resu lts of this model showed that GCOPs were well represented by our model, which could be help ful for understanding the treestructure: basic framework of PINs. Source code and binaries freely available for download at http://cic.scu. edu.cn/bioinformatics/STM/STM_code.rar.展开更多
Wireless Sensor Networks (WSNs) have inherent and unique characteristics rather than traditional networks. They have many different constraints, such as computational power, storage capacity, energy supply and etc;of ...Wireless Sensor Networks (WSNs) have inherent and unique characteristics rather than traditional networks. They have many different constraints, such as computational power, storage capacity, energy supply and etc;of course the most important issue is their energy constraint. Energy aware routing protocol is very important in WSN, but routing protocol which only considers energy has not efficient performance. Therefore considering other parameters beside energy efficiency is crucial for protocols efficiency. Depending on sensor network application, different parameters can be considered for its protocols. Congestion management can affect routing protocol performance. Congestion occurrence in network nodes leads to increasing packet loss and energy consumption. Another parameter which affects routing protocol efficiency is providing fairness in nodes energy consumption. When fairness is not considered in routing process, network will be partitioned very soon and then the network performance will be decreased. In this paper a Tree based Energy and Congestion Aware Routing Protocol (TECARP) is proposed. The proposed protocol is an energy efficient routing protocol which tries to manage congestion and to provide fairness in network. Simulation results shown in this paper imply that the TECARP has achieved its goals.展开更多
In this paper a new modeling framework for the dependability analysis of complex systems is presented and related to dynamic fault trees (DFTs). The methodology is based on a modular approach: two separate models are ...In this paper a new modeling framework for the dependability analysis of complex systems is presented and related to dynamic fault trees (DFTs). The methodology is based on a modular approach: two separate models are used to handle, the fault logic and the stochastic dependencies of the system. Thus, the fault schema, free of any dependency logic, can be easily evaluated, while the dependency schema allows the modeler to design new kind of non-trivial dependencies not easily caught by the traditional holistic methodologies. Moreover, the use of a dependency schema allows building a pure behavioral model that can be used for various kinds of dependability studies. In the paper is shown how to build and integrate the two modular models and convert them in a Stochastic Activity Network. Furthermore, based on the construction of the schema that embeds the stochastic dependencies, the procedure to convert DFTs into static fault trees is shown, allowing the resolution of DFTs in a very efficient way.展开更多
文摘This paper presents not only practical but also instructive mathematical models to simulate tree network formation using the Poisson equation and the Finite Difference Method (FDM). Then, the implications for entropic theories are discussed from the viewpoint of Maximum Entropy Production (MEP). According to the MEP principle, open systems existing in the state far from equilibrium are stabilized when entropy production is maximized, creating dissipative structures with low entropy such as the tree-shaped network. We prepare two simulation models: one is the Poisson equation model that simulates the state far from equilibrium, and the other is the Laplace equation model that simulates the isolated state or the state near thermodynamic equilibrium. The output of these equations is considered to be positively correlated to entropy production of the system. Setting the Poisson equation model so that entropy production is maximized, tree network formation is advanced. We suppose that this is due to the invocation of the MEP principle, that is, entropy of the system is lowered by emitting maximal entropy out of the system. On the other hand, tree network formation is not observed in the Laplace equation model. Our simulation results will offer the persuasive evidence that certifies the effect of the MEP principle.
基金supported by the Macao Foundation under Grant No.0249National Natural Science Foundation of China under Grant No.70901050
文摘The nestedness property has become an increasingly important means for devising efficient algorithms for network location problems.There have been attempts to explore the nestedness property of network location problems with some special cases of the convex ordered median objectives.However,there is little research on the nestedness property for those problems with the concave ordered median objectives.This paper constructs a tree network T and shows that the nestedness property cannot hold for the concave ordered median problem,which fills a gap in the research on the nestedness property.Finally,the authors pose an open problem on identifying the nestedness property for the continuous strategic ordered median problem.
文摘The sensor virus is a serious threat,as an attacker can simply send a single packet to compromise the entire sensor network.Epidemics become drastic with link additions among sensors when the small world phenomena occur.Two immunization strategies,uniform immunization and temporary immunization,are conducted on small worlds of tree-based wireless sensor networks to combat the sensor viruses.With the former strategy,the infection extends exponentially,although the immunization effectively reduces the contagion speed.With the latter strategy,recurrent contagion oscillations occur in the small world when the spatial-temporal dynamics of the epidemic are considered.The oscillations come from the small-world structure and the temporary immunization.Mathematical analyses on the small world of the Cayley tree are presented to reveal the epidemic dynamics with the two immunization strategies.
基金Supported in part by the National Natural Science Foundation of China (No.60272046, No.60102011), Na-tional High Technology Project of China (No.2002AA143010), Natural Science Foundation of Jiangsu Province (No.BK2001042), and the Foundation for Excellent Doctoral Dissertation of Southeast Univer-sity (No.YBJJ0412).
文摘Several data mining techniques such as Hidden Markov Model (HMM), artificial neural network, statistical techniques and expert systems are used to model network packets in the field of intrusion detection. In this paper a novel intrusion detection mode based on understandable Neural Network Tree (NNTree) is pre-sented. NNTree is a modular neural network with the overall structure being a Decision Tree (DT), and each non-terminal node being an Expert Neural Network (ENN). One crucial advantage of using NNTrees is that they keep the non-symbolic model ENN’s capability of learning in changing environments. Another potential advantage of using NNTrees is that they are actually “gray boxes” as they can be interpreted easily if the num-ber of inputs for each ENN is limited. We showed through experiments that the trained NNTree achieved a simple ENN at each non-terminal node as well as a satisfying recognition rate of the network packets dataset. We also compared the performance with that of a three-layer backpropagation neural network. Experimental results indicated that the NNTree based intrusion detection model achieved better performance than the neural network based intrusion detection model.
文摘Fetal distress is one of the main factors to cesarean section in obstetrics and gynecology. If the fetus lack of oxygen in uterus, threat to the fetal health and fetal death could happen. Cardiotocography (CTG) is the most widely used technique to monitor the fetal health and fetal heart rate (FHR) is an important index to identify occurs of fetal distress. This study is to propose discriminant analysis (DA), decision tree (DT), and artificial neural network (ANN) to evaluate fetal distress. The results show that the accuracies of DA, DT and ANN are 82.1%, 86.36% and 97.78%, respectively.
基金Supported by the National Natural Science Foundation of China(81372358,81527801,51303140,and 81602489)the Natural Science Foundation of Hubei Province(2014CFA029)+1 种基金the Colleges of Hubei Province Outstanding Youth Science and Technology Innovation Team(T201305)the Applied Foundational Research Program of Wuhan Municipal Science and Technology Bureau(2015060101010056)
文摘This paper describes a simple method of generating concentration gradients with linear and parabolic profiles by using a Christmas tree-shaped microfluidic network.The microfluidic gradient generator consists of two parts：a Christmas tree-shaped network for gradient generation and a broad microchannel for detection.A two-dimensional model was built to analyze the flow field and the mass transfer in the microfluidic network.The simulating results show that a series of linear and parabolic gradient profiles were generated via adjusting relative flow rate ratios of the two source solutions（R_L^2≥0.995 and _PR^2≥0.999）,which could match well with the experimental results（R_L^2≥0.987 and _PR^2≥0.996）.The proposed method is promising for the generation of linear and parabolic concentration gradient profiles,with the potential in chemical and biological applications such as combinatorial chemistry synthesis,stem cell differentiation or cytotoxicity assays.
基金College of Agriculture and Natural Resources,University of Tehran for financial support of the study(Grant No.7104017/6/24 and 28)
文摘To build any spatial soil database, a set of environmental data including digital elevation model(DEM) and satellite images beside geomorphic landscape description are essentials. Such a database, integrates field observations and laboratory analyses data with the results obtained from qualitative and quantitative models. So far, various techniques have been developed for soil data processing. The performance of Artificial Neural Network(ANN) and Decision Tree(DT) models was compared to map out some soil attributes in Alborz Province, Iran. Terrain attributes derived from a DEM along with Landsat 8 ETM+, geomorphology map, and the routine laboratory analyses of the studied area were used as input data. The relationships between soil properties(including sand, silt, clay, electrical conductivity, organic carbon, and carbonates) and the environmental variables were assessed using the Pearson Correlation Coefficient and Principle Components Analysis. Slope, elevation, geomforms, carbonate index, stream network, wetness index, and the band’s number 2, 3, 4, and 5 were the most significantly correlated variables. ANN and DT did not show the same accuracy in predicting all parameters. The DT model showed higher performances in estimating sand(R^2=0.73), silt(R^2=0.70), clay(R^2=0.72), organic carbon(R^2=0.71), and carbonates(R^2=0.70). While the ANN model only showed higher performance in predicting soil electrical conductivity(R^2=0.95). The results showed that determination the best model to use, is dependent upon the relation between the considered soil properties with the environmental variables. However, the DT model showed more reasonable results than the ANN model in this study. The results showed that before using a certain model to predict variability of all soil parameters, it would be better to evaluate the efficiency of all possible models for choosing the best fitted model for each property. In other words, most of the developed models are sitespecific and may not be applicable to use for predicting other soil properties or other area.
文摘The Wireless Sensor Network (WSN) is spatially distributed autonomous sensor to sense special task. WSN like ZigBee network forms simple interconnecting, low power, and low processing capability wireless devices. The ZigBee devices facilitate numerous applications such as pervasive computing, security monitoring and control. ZigBee end devices collect sensing data and send them to ZigBee Coordinator. The Coordinator processes end device requests. The effect of a large number of random unsynchronized requests may degrade the overall network performance. An effective technique is particularly needed for synchronizing available node’s request processing to design a reliable ZigBee network. In this paper, region based priority mechanism is implemented to synchronize request with Tree Routing Method. Riverbed is used to simulate and analyze overall ZigBee network performance. The results show that the performance of the overall priority based ZigBee network model is better than without a priority based model. This research paves the way for further designing and modeling a large scale ZigBee network.
基金The Hong Kong Polytechnic University under internal Grant No. G-YF51.
文摘In a sensor network with a large number of densely populated sensor nodes, a single target of interest may be detected by multiple sensor nodes simultaneously. Data collected from the sensor nodes are usually highly correlated, and hence energy saving using in-network data fusion becomes possible. A traditional data fusion scheme starts with dividing the network into clusters, followed by electing a sensor node as cluster head in each cluster. A cluster head is responsible for collecting data from all its cluster members, performing data fusion on these data and transmitting the fused data to the base station. Assuming that a sensor node is only capable of handling a single node-to-node transmission at a time and each transmission takes T time-slots, a cluster head with n cluster members will take at least nT time-slots to collect data from all its cluster members. In this paper, a tree-based network structure and its formation algorithms are proposed. Simulation results show that the proposed network structure can greatly reduce the delay in data collection.
基金National Natural Science Foundation of China （60532030, 10577005, 60625102） Innovation Foundation of Aerospace Science and Technology of China
文摘A new core-based shared tree algorithm, viz core-cluster combination-based shared tree （CCST） algorithm and the weighted version （i.e. w-CCST algorithm） are proposed in order to resolve the channel resources waste problem in typical source-based multicast routing algorithms in low earth orbit （LEO） satellite IP networks. The CCST algorithm includes the dynamic approximate center （DAC） core selection method and the core-cluster combination multicast route construction scheme. Without complicated onboard computation, the DAC method is uniquely developed for highly dynamic networks of periodical and regular movement. The core-cluster combination method takes core node as the initial core-cluster, and expands it stepwise to construct an entire multicast tree at the lowest tree cost by a shortest path scheme between the newly-generated core-cluster and surplus group members, which results in great bandwidth utilization. Moreover, the w-CCST algorithm is able to strike a balance between performance of tree cost and that of end-to-end propagation delay by adjusting the weighted factor to meet strict end-to-end delay requirements of some real-time multicast services at the expense of a slight increase in tree cost. Finally, performance comparison is conducted between the proposed algorithms and typical algorithms in LEO satellite IP networks. Simulation results show that the CCST algorithm significantly decreases the average tree cost against to the others, and also the average end-to-end propagation delay ofw-CCST algorithm is lower than that of the CCST algorithm.
基金supported by the National Natural Science Fundation of China (6097408261075055)the Fundamental Research Funds for the Central Universities (K50510700004)
文摘The learning Bayesian network （BN） structure from data is an NP-hard problem and still one of the most exciting chal- lenges in the machine learning. In this work, a novel algorithm is presented which combines ideas from local learning, constraint- based, and search-and-score techniques in a principled and ef- fective way. It first reconstructs the junction tree of a BN and then performs a K2-scoring greedy search to orientate the local edges in the cliques of junction tree. Theoretical and experimental results show the proposed algorithm is capable of handling networks with a large number of variables. Its comparison with the well-known K2 algorithm is also presented.
基金Project supported by the State Key Development Program for Basic Research of China (Grant No 2006CB708612)the National Natural Science Foundation of China (Grant No 10572130)the Natural Science Foundation of Zhejiang Province, China (Grant No Y607425)
文摘Asymmetric tree-like branched networks are explored by geometric algorithms. Based on the network, an analysis of the thermal conductivity is presented. The relationship between effective thermal conductivity and geometric structures is obtained by using the thermal-electrical analogy technique. In all studied cases, a clear behaviour is observed, where angle （δ,θ） among parent branching extended lines, branches and parameter of the geometric structures have stronger effects on the effective thermal conductivity. When the angle δ is fixed, the optical diameter ratio β＋ is dependent on angle θ. Moreover, γand m are not related to β＊. The longer the branch is, the smaller the effective thermal conductivity will be. It is also found that when the angle θ〈δ2, the higher the iteration m is, the lower the thermal conductivity will be and it tends to zero, otherwise, it is bigger than zero. When the diameter ratio β1 〈 0.707 and angle δ is bigger, the optimal k of the perfect ratio increases with the increase of the angle δ; when β1 〉 0.707, the optimal k decreases. In addition, the effective thermal conductivity is always less than that of single channel material. The present results also show that the effective thermal conductivity of the asymmetric tree-like branched networks does not obey Murray＇s law.
文摘In this work, a hardware intrusion detection system （IDS） model and its implementation are introduced to perform online real-time traffic monitoring and analysis. The introduced system gathers some advantages of many IDSs： hardware based from implementation point of view, network based from system type point of view, and anomaly detection from detection approach point of view. In addition, it can detect most of network attacks, such as denial of services （DOS）, leakage, etc. from detection behavior point of view and can detect both internal and external intruders from intruder type point of view. Gathering these features in one IDS system gives lots of strengths and advantages of the work. The system is implemented by using field programmable gate array （FPGA）, giving a more advantages to the system. A C5.0 decision tree classifier is used as inference engine to the system and gives a high detection ratio of 99.93%.
基金The Research of Key Technology and Application of Information Security Certification Project(No.2016YFF0204001)
文摘Network security equipment is crucial to information systems, and a proper evaluation model can ensure the quality of network security equipment. However, there is only a few models of comprehensive models nowadays. An index system for network security equipment was established and a model based on attack tree with risk fusion was proposed to obtain the score of qualitative indices. The proposed model implements attack tree model and controlled interval and memory(CIM) model to solve the problem of quantifying qualitative indices, and thus improves the accuracy of the evaluation.
基金supported by the National Natural Science Foundation of China (Grant No. 50869005)
文摘Tree ring dating plays an important role in obtaining past climate information.The fundamental study of obtaining tree ring samples in typical climate regions is particularly essential.The optimum distribution of tree ring sampling sites based on climate information from the Climate Observation Network(ORPOM model) is presented in this article.In this setup,the tree rings in a typical region are used for surface representation,by applying excellent correlation with the climate information as the main principle.Taking the Horqin Sandy Land in the cold and arid region of China as an example,the optimum distribution range of the tree ring sampling sites was obtained through the application of the ORPOM model,which is considered a reasonably practical scheme.
基金Project supported by the National Natural Science Foundation of China （Grant Nos.10471088, 60572126）
文摘A finite random graph generated by continuous time birth and death processes with exponentially distributed waiting times was investigated, which is similar to a communication network in daily life. The vertices are the living particles, and directed edges go from mothers to daughters. The size of the communication network was studied. Furthermore, the probability of successfully connecting senders with receivers and the transmitting speed of information were obtained.
文摘In living cells, proteins are dynamically connec ted through biochemical reactions, so its functi onal features are properly encoded into protein protein interaction networks (PINs). Up to pres ent, many efforts have been devoted to exploring the basic feature of PINs. However, it is still a challenging problem to explore a universal pr operty of PINs. Here we employed the complex networks theory to analyze the proteinprotein interactions from Database of Interacting Prot ein. Complex tree: the unique framework of PINs was revealed by three topological properties of the giant component of PINs (GCOP), including rightskewed degree distributions, relatively sm all clustering coefficients and short characteristic path lengths. Furthermore, we proposed a no nlinearly growth model: complex tree model to reflect the tree framework, the simulation resu lts of this model showed that GCOPs were well represented by our model, which could be help ful for understanding the treestructure: basic framework of PINs. Source code and binaries freely available for download at http://cic.scu. edu.cn/bioinformatics/STM/STM_code.rar.
文摘Wireless Sensor Networks (WSNs) have inherent and unique characteristics rather than traditional networks. They have many different constraints, such as computational power, storage capacity, energy supply and etc;of course the most important issue is their energy constraint. Energy aware routing protocol is very important in WSN, but routing protocol which only considers energy has not efficient performance. Therefore considering other parameters beside energy efficiency is crucial for protocols efficiency. Depending on sensor network application, different parameters can be considered for its protocols. Congestion management can affect routing protocol performance. Congestion occurrence in network nodes leads to increasing packet loss and energy consumption. Another parameter which affects routing protocol efficiency is providing fairness in nodes energy consumption. When fairness is not considered in routing process, network will be partitioned very soon and then the network performance will be decreased. In this paper a Tree based Energy and Congestion Aware Routing Protocol (TECARP) is proposed. The proposed protocol is an energy efficient routing protocol which tries to manage congestion and to provide fairness in network. Simulation results shown in this paper imply that the TECARP has achieved its goals.
文摘In this paper a new modeling framework for the dependability analysis of complex systems is presented and related to dynamic fault trees (DFTs). The methodology is based on a modular approach: two separate models are used to handle, the fault logic and the stochastic dependencies of the system. Thus, the fault schema, free of any dependency logic, can be easily evaluated, while the dependency schema allows the modeler to design new kind of non-trivial dependencies not easily caught by the traditional holistic methodologies. Moreover, the use of a dependency schema allows building a pure behavioral model that can be used for various kinds of dependability studies. In the paper is shown how to build and integrate the two modular models and convert them in a Stochastic Activity Network. Furthermore, based on the construction of the schema that embeds the stochastic dependencies, the procedure to convert DFTs into static fault trees is shown, allowing the resolution of DFTs in a very efficient way.
