Simulations of water flow in channel networks require estimated values of roughness for all the individual channel segments that make up a network. When the number of individual channel segments is large, the paramete...Simulations of water flow in channel networks require estimated values of roughness for all the individual channel segments that make up a network. When the number of individual channel segments is large, the parameter calibration workload is substantial and a high level of uncertainty in estimated roughness cannot be avoided. In this study, all the individual channel segments are graded according to the factors determining the value of roughness. It is assumed that channel segments with the same grade have the same value of roughness. Based on observed hydrological data, an optimal model for roughness estimation is built. The procedure of solving the optimal problem using the optimal model is described. In a test of its efficacy, this estimation method was applied successfully in the simulation of tidal water flow in a large complicated channel network in the lower reach of the Yangtze River in China.展开更多
Aiming at the problems of low detection accuracy and large model size of existing object detection algorithms applied to complex road scenes,an improved you only look once version 8(YOLOv8)object detection algorithm f...Aiming at the problems of low detection accuracy and large model size of existing object detection algorithms applied to complex road scenes,an improved you only look once version 8(YOLOv8)object detection algorithm for infrared images,F-YOLOv8,is proposed.First,a spatial-to-depth network replaces the traditional backbone network's strided convolution or pooling layer.At the same time,it combines with the channel attention mechanism so that the neural network focuses on the channels with large weight values to better extract low-resolution image feature information;then an improved feature pyramid network of lightweight bidirectional feature pyramid network(L-BiFPN)is proposed,which can efficiently fuse features of different scales.In addition,a loss function of insertion of union based on the minimum point distance(MPDIoU)is introduced for bounding box regression,which obtains faster convergence speed and more accurate regression results.Experimental results on the FLIR dataset show that the improved algorithm can accurately detect infrared road targets in real time with 3%and 2.2%enhancement in mean average precision at 50%IoU(mAP50)and mean average precision at 50%—95%IoU(mAP50-95),respectively,and 38.1%,37.3%and 16.9%reduction in the number of model parameters,the model weight,and floating-point operations per second(FLOPs),respectively.To further demonstrate the detection capability of the improved algorithm,it is tested on the public dataset PASCAL VOC,and the results show that F-YOLO has excellent generalized detection performance.展开更多
A coupled one-dimensional （1-D） and two-dimensional （2-D） channel network mathematical model is proposed for flow calculations at nodes in a channel network system in this article. For the 1-D model, the finite di...A coupled one-dimensional （1-D） and two-dimensional （2-D） channel network mathematical model is proposed for flow calculations at nodes in a channel network system in this article. For the 1-D model, the finite difference method is used to discretize the Saint-Venant equations in all channels of a looped network. The Alternating Direction Implicit （ADI） method is adopted for the 2-D model at the nodes. In the coupled model, the 1-D model provides a good approximation with small computational effort, while the 2-D model is applied for complex topography to achieve a high accuracy. An Artificial Neural Network （ANN.） method is used for the data exchange and the connectivity between the 1-D and 2-D models. The coupled model is applied to the Jingjiang-Dongting Lake region, to simulate the tremendous looped channel network system, and the results are compared with field data. The good agreement shows that the coupled hydraulic model is more effective than the conventional 1-D model.展开更多
Payment Channel Networks(PCNs)are a promising alternative to improve the scalability of a blockchain network.A PCN employs off-chain micropayment channels that do not need a global block confirmation procedure,thereby...Payment Channel Networks(PCNs)are a promising alternative to improve the scalability of a blockchain network.A PCN employs off-chain micropayment channels that do not need a global block confirmation procedure,thereby sacrificing the ability to confirm transactions instantaneously.PCN uses a routing algorithm to identify a path between two users who do not have a direct channel between them to settle a transaction.The performance of most of the existing centralized path-finding algorithms does not scale with network size.The rapid growth of Bitcoin PCN necessitates considering distributed algorithms.However,the existing decentralized algorithms suffer from resource underutilization.We present a decentralized routing algorithm,Swift,focusing on fee optimization.The concept of a secret path is used to reduce the path length between a sender and a receiver to optimize the fees.Furthermore,we reduce a network structure into combinations of cycles to theoretically study fee optimization with changes in cloud size.The secret path also helps in edge load sharing,which results in an improvement of throughput.Swift routing achieves up to 21%and 63%in fee and throughput optimization,respectively.The results from the simulations follow the trends identified in the theoretical analysis.展开更多
Scalability has long been a major challenge of cryptocurrency systems,which is mainly caused by the delay in reaching consensus when processing transactions on-chain.As an effective mitigation approach,the payment cha...Scalability has long been a major challenge of cryptocurrency systems,which is mainly caused by the delay in reaching consensus when processing transactions on-chain.As an effective mitigation approach,the payment channel networks(PCNs)enable private channels among blockchain nodes to process transactions off-chain,relieving long-time waiting for the online transaction confirmation.The state-of-the-art studies of PCN focus on improving the efficiency and availability via optimizing routing,scheduling,and initial deposits,as well as preventing the system from security and privacy attacks.However,the behavioral decision dynamics of blockchain nodes under potential malicious attacks is largely neglected.To fill this gap,we employ the game theory to study the characteristics of channel interactions from both the micro and macro perspectives under the situation of channel depletion attacks.Our study is progressive,as we conduct the game-theoretic analysis of node behavioral characteristics from individuals to the whole population of PCN.Our analysis is complementary,since we utilize not only the classic game theory with the complete rationality assumption,but also the evolutionary game theory considering the limited rationality of players to portray the evolution of PCN.The results of numerous simulation experiments verify the effectiveness of our analysis.展开更多
Payment Channel Network(PCN)provides the off-chain settlement of transactions.It is one of the most promising solutions to solve the scalability issue of the blockchain.Many routing techniques in PCN have been propose...Payment Channel Network(PCN)provides the off-chain settlement of transactions.It is one of the most promising solutions to solve the scalability issue of the blockchain.Many routing techniques in PCN have been proposed.However,both incentive attack and privacy protection have not been considered in existing studies.In this paper,we present an auction-based system model for PCN routing using the Laplace differential privacy mechanism.We formulate the cost optimization problem to minimize the path cost under the constraints of the Hashed Time-Lock Contract(HTLC)tolerance and the channel capacity.We propose an approximation algorithm to find the top K shortest paths constrained by the HTLC tolerance and the channel capacity,i.e.,top K-restricted shortest paths.Besides,we design the probability comparison function to find the path with the largest probability of having the lowest path cost among the top K-restricted shortest paths as the final path.Moreover,we apply the binary search to calculate the transaction fee of each user.Through both theoretical analysis and extensive simulations,we demonstrate that the proposed routing mechanism can guarantee the truthfulness and individual rationality with the probabilities of 1/2 and 1/4,respectively.It can also ensure the differential privacy of the users.The experiments on the real-world datasets demonstrate that the privacy leakage of the proposed mechanism is 73.21%lower than that of the unified privacy protection mechanism with only 13.2%more path cost compared with the algorithm without privacy protection on average.展开更多
In this work,a frame work for time-varying channel modeling and simulation is proposed by using neural network(NN)to overcome the shortcomings in geometry based stochastic model(GBSM)and simulation approach.Two NN mod...In this work,a frame work for time-varying channel modeling and simulation is proposed by using neural network(NN)to overcome the shortcomings in geometry based stochastic model(GBSM)and simulation approach.Two NN models are developed for modeling of path loss together with shadow fading(SF)and joint small scale channel parameters.The NN models can predict path loss plus SF and small scale channel parameters accurately compared with measurement at 26 GHz performed in an outdoor microcell.The time-varying path loss and small scale channel parameters generated by the NN models are proposed to replace the empirical path loss and channel parameter random numbers in GBSM-based framework to playback the measured channel and match with its environment.Moreover,the sparse feature of clusters,delay and angular spread,channel capacity are investigated by a virtual array measurement at 28 GHz in a large waiting hall.展开更多
Wireless sensor networks are suffering from serious frequency interference.In this paper,we propose a channel assignment algorithm based on graph theory in wireless sensor networks.We first model the conflict infectio...Wireless sensor networks are suffering from serious frequency interference.In this paper,we propose a channel assignment algorithm based on graph theory in wireless sensor networks.We first model the conflict infection graph for channel assignment with the goal of global optimization minimizing the total interferences in wireless sensor networks.The channel assignment problem is equivalent to the generalized graph-coloring problem which is a NP-complete problem.We further present a meta-heuristic Wireless Sensor Network Parallel Tabu Search(WSN-PTS) algorithm,which can optimize global networks with small numbers of iterations.The results from a simulation experiment reveal that the novel algorithm can effectively solve the channel assignment problem.展开更多
Along with the surge of unearthed medical literature and cultural relics in recent years,a network of channels in the system of medical conduit vessels(meridians) during the early Western Han dynasty has become much c...Along with the surge of unearthed medical literature and cultural relics in recent years,a network of channels in the system of medical conduit vessels(meridians) during the early Western Han dynasty has become much clearer gradually.In it,the increasing number of channel branches,network vessels and needle insertion holes(acupoints) is an important feature of the development of channel medicine during the Western Han dynasty.This is not only a reflection of the expanding requirements of the theoretical system of the main trunk channels and other vessels,but also an inevitable result of the continuous enrichment and accumulation of clinical experience.This article integrates the information about channel branches,network vessels,inscriptions,dots and further relics on the Tianhui(天回) Lacquered Meridian Figurine to compare the unearthed literature of the channel genre with the transmitted classical literature about acupuncture.The “Heart-Regulated Channel” in Medical Manuscripts on Bamboo Slips from Tianhui(《天回医简》) serves as an example to explain the occurrence,development and changes of the channel branches and network vessels in the early system of medical channels.展开更多
Employing multiple channels in wireless multihop networks is regarded as an effective approach to increas-ing network capacity. This paper presents a centralized quasi-static channel assignment for multi-radio multi-c...Employing multiple channels in wireless multihop networks is regarded as an effective approach to increas-ing network capacity. This paper presents a centralized quasi-static channel assignment for multi-radio multi-channel Wireless Mesh Networks (WMNs). The proposed channel assignment can efficiently utilize multiple channels with only 2 radios equipped on each mesh router. In the scheme, the network end-to-end traffics are first modeled by probing data at wireless access points, and then the traffic load between each pair of neighboring routers is further estimated using an interference-aware estimation algorithm. Having knowledge of the expected link load, the scheme assigns channels to each radio with the objective of mini-mizing network interference, which as a result greatly improves network capacity. The performance evalua-tion shows that the proposed scheme is highly responsive to varying traffic conditions, and the network per-formance under the channel assignment significantly outperforms the single-radio IEEE 802.11 network as well as the 2-radio WMN with static 2 channels.展开更多
We numerically study the effect of the channel noise on the spiking synchronization of a scale-free Hodgkin-Huxley neuron network with time delays. It is found that the time delay can induce synchronization transition...We numerically study the effect of the channel noise on the spiking synchronization of a scale-free Hodgkin-Huxley neuron network with time delays. It is found that the time delay can induce synchronization transitions at an intermediate and proper channel noise intensity, and the synchronization transitions become strongest when the channel noise intensity is optimal. The neurons can also exhibit synchronization transitions as the channel noise intensity is varied, and this phenomenon is enhanced at around the time delays that can induce the synchronization transitions. It is also found that the synchronization transitions induced by the channel noise are dependent on the coupling strength and the network average degree, and there is an optimal coupling strength or network average degree with which the synchronization transitions become strongest. These results show that by inducing synchronization transitions, the channel noise has a big regulation effect on the synchronization of the neuronal network. These findings could find potential implications for the information transmission in neural systems.展开更多
In a wireless sensor network （WSN）, the energy of nodes is limited and cannot be charged. Hence, it is necessary to reduce energy consumption. Both the transmission power of nodes and the interference among nodes in...In a wireless sensor network （WSN）, the energy of nodes is limited and cannot be charged. Hence, it is necessary to reduce energy consumption. Both the transmission power of nodes and the interference among nodes influence energy consumption. In this paper, we design a power control and channel allocation game model with low energy consumption （PCCAGM）. This model contains transmission power, node interference, and residual energy. Besides, the interaction between power and channel is considered. The Nash equilibrium has been proved to exist. Based on this model, a power control and channel allocation optimization algorithm with low energy consumption （PCCAA） is proposed. Theoretical analysis shows that PCCAA can converge to the Pareto Optimal. Simulation results demonstrate that this algorithm can reduce transmission power and interference effectively. Therefore, this algorithm can reduce energy consumption and prolong the network lifetime.展开更多
In this paper pilot based channel estimation is being considered for broadband power line communication (BPLC) networks witch used orthogonal frequency division multiplexing (OFDM) in order to transmit high rate data....In this paper pilot based channel estimation is being considered for broadband power line communication (BPLC) networks witch used orthogonal frequency division multiplexing (OFDM) in order to transmit high rate data. To estimate channel in time or frequency some pilot must be used. Number of these pilots and deployment of them is very important for proper estimation in different channel with varying time and frequency. Carrier sense multiple access (CSMA) and hybrid multiple access protocol are taken into consideration in MAC sub-layer. Multilayered perceptions neural network with backpropagation (BP) learning channel estimator algorithm with different pilot deployment compare to classic algorithm in for channel estimating. Simulation results show the proposed neural network estimation decreases bit error rate and therefore network throughput increases.展开更多
Network Coding (NC) is confirmed to be power and bandwidth efficient technique, because of the less number of transmitted packets over the network. Wireless Sensor Network (WSN) is usually power limited network applic...Network Coding (NC) is confirmed to be power and bandwidth efficient technique, because of the less number of transmitted packets over the network. Wireless Sensor Network (WSN) is usually power limited network application, and in many scenarios it is power and bandwidth limited application. The proposed scenario in this paper applies the advantages of NC over WSN to obtain such power and bandwidth efficient WSN. To take the advantages of NC over the one of the most needed applications i.e., WSN, we come up to what this paper is discussing. We consider a WSN (or its cluster) that consists of M nodes that transmit equal-length information packets to a common destination node D over wireless Rayleigh block-fading channel where the instantaneous SNR is assumed to be constant over a single packet transmission period. Finite-State packet level Markov chain (FSMC) model is applied to give the channel more practical aspect. The simulation results showed that applying NC over the WSN cluster improved the channel bandwidth significantly by decreasing the number of the Automatic Repeat Request (ARQ), resulting in improving the power consumption significantly. The results are collected for different transmission distances to evaluate the behavior to the proposed scenario with regard to the bath losses effect.展开更多
Relay in full-duplex(FD) mode can achieve higher spectrum efficiency than that in half-duplex mode,while it is crucial to suppress relay self-interference to ensure transmission quality which requires instantaneous ch...Relay in full-duplex(FD) mode can achieve higher spectrum efficiency than that in half-duplex mode,while it is crucial to suppress relay self-interference to ensure transmission quality which requires instantaneous channel state information(CSI). In this paper,the channel estimation issue in FD amplify-andforward relay networks is considered,where the training-based estimation technique is adopted. Firstly,the least square(LS) estimation is implemented to obtain composite channel coefficients of source-relay-destination(SRD) channel and relay loop-interference(LI) channel in order to assist destination in performing data detection. Secondly,both LS and maximum likelihood estimation methods are utilized to perform individual channel estimation aiming at supporting successive interference cancelation at destination. Finally,simulation results demonstrate the effectiveness of both composite and individual channel estimation,and the presented ML method can achieve lower MSEs than LS solution.展开更多
Network coding (NC), introduced at the turn of the century, enables nodes in a network to combine data algebraically before either sending or forwarding them. Random network coding has gained popularity over the years...Network coding (NC), introduced at the turn of the century, enables nodes in a network to combine data algebraically before either sending or forwarding them. Random network coding has gained popularity over the years by combining the received packet randomly before forwarding them, resulting in a complex Jordan Gaussian Elimination (JGE) decoding process. The effectiveness of random NC is through cooperation among nodes. In this paper, we propose a simple, low-complexity cooperative protocol that exploits NC in a deterministic manner resulting in improved diversity, data rate, and less complex JGE decoding process. The proposed system is applied over a lossy wireless network. The scenario under investigation is as follows: M users must send their information to a common destination D and to exchange the information between each others, over erasure channels;typically the channels between the users and the destination are worse than the channels between users. It is possible to significantly reduce the traffic among users and destination, achieving significant bandwidth savings, by combining packets from different users in simple, deterministic ways without resorting to extensive header information before being forwarded to the destination and the M users. The key problem we try to address is how to efficiently combine the packets at each user while exploiting user cooperation and the probability of successfully recovering information from all users at D with k < 2M unique linear equations, accounting for the fact that the remaining packets will be lost in the network and there are two transmission stages. Simulation results show the behaviour for two and three transmission stages. Our results show that applying NC protocols in two or three stages decreases the traffic significantly, beside the fact that the proposed protocols enable the system to retrieve the lost packets rather than asking for ARQ, resulting in improved data flow, and less power consumption. In fact, in some protocols the ARQ dropped from the rate 10ˉ<sup>1</sup> to 10ˉ<sup>4</sup>, because of the proposed combining algorithm that enables the nodes to generate additional unique linear equations to broadcast rather than repeating the same ones via ARQ. Moreover, the number of the transmitted packets in each cooperative stage dropped from M (M - 1) to just M packets, resulting to 2 M packets instead 2 (M<sup>2</sup> - 1) when three stages of transmission system are used instead of one stage (two cooperative stages).展开更多
While all-optical networks become more and more popular as the basis of the next generation Internet(NGI)infrastructure,such networks raise many critical security issues.High power inter-channel crosstalk attack is on...While all-optical networks become more and more popular as the basis of the next generation Internet(NGI)infrastructure,such networks raise many critical security issues.High power inter-channel crosstalk attack is one of the security issues which have negative effect on information security in optical networks.Optical fiber in optical networks has some nonlinear characteristics,such as self phase modulation(SPM),cross phase modulation(XPM),four-wave mixing(FWM)and stimulated Raman scattering(SRS).They can be used to implement high power inter-channel crosstalk attack by malicious attackers.The mechanism of high power inter-channel crosstalk attack is analyzed.When an attack occurs,attack signal power and fiber nonlinear refractive index are the main factors which affect quality of legitimate signals.The effect of high power inter-channel crosstalk attack on quality of legitimate signals is investigated by building simulation system in VPI software.The results show that interchannel crosstalk caused by high power attack signal leads to quality deterioration of legitimate signals propagated in the same fiber.The higher the power of attack signal is,the greater the fiber nonlinear refractive index is.The closer the channel spacing away from the attack signal is,the more seriously the legitimate signals are affected by attack.We also find that when attack position and power of attack signal are constant,attack signal cannot infinitely spread,while its attack ability shows a fading trend with the extension of propagation distance.展开更多
The algorithm for VLSI channel routing using Hopfield neural model is discussed inthis paper.The basic methods of mapping VLSI channel routing problem to Hopfield neural net-work,constructing energy function,setting i...The algorithm for VLSI channel routing using Hopfield neural model is discussed inthis paper.The basic methods of mapping VLSI channel routing problem to Hopfield neural net-work,constructing energy function,setting initial neural status,and selecting various parametersare proposed.Finally,some experimental results are given.展开更多
Despite extensive research, timing channels (TCs) are still known as a principal category of threats that aim to leak and transmit information by perturbing the timing or ordering of events. Existing TC detection appr...Despite extensive research, timing channels (TCs) are still known as a principal category of threats that aim to leak and transmit information by perturbing the timing or ordering of events. Existing TC detection approaches use either signature-based approaches to detect known TCs or anomaly-based approach by modeling the legitimate network traffic in order to detect unknown TCs. Un-fortunately, in a software-defined networking (SDN) environment, most existing TC detection approaches would fail due to factors such as volatile network traffic, imprecise timekeeping mechanisms, and dynamic network topology. Furthermore, stealthy TCs can be designed to mimic the legitimate traffic pattern and thus evade anomalous TC detection. In this paper, we overcome the above challenges by presenting a novel framework that harnesses the advantages of elastic re-sources in the cloud. In particular, our framework dynamically configures SDN to enable/disable differential analysis against outbound network flows of different virtual machines (VMs). Our framework is tightly coupled with a new metric that first decomposes the timing data of network flows into a number of using the discrete wavelet-based multi-resolution transform (DWMT). It then applies the Kullback-Leibler divergence (KLD) to measure the variance among flow pairs. The appealing feature of our approach is that, compared with the existing anomaly detection approaches, it can detect most existing and some new stealthy TCs without legitimate traffic for modeling, even with the presence of noise and imprecise timekeeping mechanism in an SDN virtual environment. We implement our framework as a prototype system, OBSERVER, which can be dynamically deployed in an SDN environment. Empirical evaluation shows that our approach can efficiently detect TCs with a higher detection rate, lower latency, and negligible performance overhead compared to existing approaches.展开更多
基金supported by the Chinese Jiangsu Provincial Natural Science Foundation (Grant No. BK2001017)
文摘Simulations of water flow in channel networks require estimated values of roughness for all the individual channel segments that make up a network. When the number of individual channel segments is large, the parameter calibration workload is substantial and a high level of uncertainty in estimated roughness cannot be avoided. In this study, all the individual channel segments are graded according to the factors determining the value of roughness. It is assumed that channel segments with the same grade have the same value of roughness. Based on observed hydrological data, an optimal model for roughness estimation is built. The procedure of solving the optimal problem using the optimal model is described. In a test of its efficacy, this estimation method was applied successfully in the simulation of tidal water flow in a large complicated channel network in the lower reach of the Yangtze River in China.
基金supported by the National Natural Science Foundation of China(No.62103298)。
文摘Aiming at the problems of low detection accuracy and large model size of existing object detection algorithms applied to complex road scenes,an improved you only look once version 8(YOLOv8)object detection algorithm for infrared images,F-YOLOv8,is proposed.First,a spatial-to-depth network replaces the traditional backbone network's strided convolution or pooling layer.At the same time,it combines with the channel attention mechanism so that the neural network focuses on the channels with large weight values to better extract low-resolution image feature information;then an improved feature pyramid network of lightweight bidirectional feature pyramid network(L-BiFPN)is proposed,which can efficiently fuse features of different scales.In addition,a loss function of insertion of union based on the minimum point distance(MPDIoU)is introduced for bounding box regression,which obtains faster convergence speed and more accurate regression results.Experimental results on the FLIR dataset show that the improved algorithm can accurately detect infrared road targets in real time with 3%and 2.2%enhancement in mean average precision at 50%IoU(mAP50)and mean average precision at 50%—95%IoU(mAP50-95),respectively,and 38.1%,37.3%and 16.9%reduction in the number of model parameters,the model weight,and floating-point operations per second(FLOPs),respectively.To further demonstrate the detection capability of the improved algorithm,it is tested on the public dataset PASCAL VOC,and the results show that F-YOLO has excellent generalized detection performance.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.10872110,10902061)
文摘A coupled one-dimensional （1-D） and two-dimensional （2-D） channel network mathematical model is proposed for flow calculations at nodes in a channel network system in this article. For the 1-D model, the finite difference method is used to discretize the Saint-Venant equations in all channels of a looped network. The Alternating Direction Implicit （ADI） method is adopted for the 2-D model at the nodes. In the coupled model, the 1-D model provides a good approximation with small computational effort, while the 2-D model is applied for complex topography to achieve a high accuracy. An Artificial Neural Network （ANN.） method is used for the data exchange and the connectivity between the 1-D and 2-D models. The coupled model is applied to the Jingjiang-Dongting Lake region, to simulate the tremendous looped channel network system, and the results are compared with field data. The good agreement shows that the coupled hydraulic model is more effective than the conventional 1-D model.
文摘Payment Channel Networks(PCNs)are a promising alternative to improve the scalability of a blockchain network.A PCN employs off-chain micropayment channels that do not need a global block confirmation procedure,thereby sacrificing the ability to confirm transactions instantaneously.PCN uses a routing algorithm to identify a path between two users who do not have a direct channel between them to settle a transaction.The performance of most of the existing centralized path-finding algorithms does not scale with network size.The rapid growth of Bitcoin PCN necessitates considering distributed algorithms.However,the existing decentralized algorithms suffer from resource underutilization.We present a decentralized routing algorithm,Swift,focusing on fee optimization.The concept of a secret path is used to reduce the path length between a sender and a receiver to optimize the fees.Furthermore,we reduce a network structure into combinations of cycles to theoretically study fee optimization with changes in cloud size.The secret path also helps in edge load sharing,which results in an improvement of throughput.Swift routing achieves up to 21%and 63%in fee and throughput optimization,respectively.The results from the simulations follow the trends identified in the theoretical analysis.
基金The work was partially supported by the National Key Research and Development Program of China under Grant No.2019YFB2102600the National Natural Science Foundation of China under Grant Nos.62122042,61971269 and 61832012.
文摘Scalability has long been a major challenge of cryptocurrency systems,which is mainly caused by the delay in reaching consensus when processing transactions on-chain.As an effective mitigation approach,the payment channel networks(PCNs)enable private channels among blockchain nodes to process transactions off-chain,relieving long-time waiting for the online transaction confirmation.The state-of-the-art studies of PCN focus on improving the efficiency and availability via optimizing routing,scheduling,and initial deposits,as well as preventing the system from security and privacy attacks.However,the behavioral decision dynamics of blockchain nodes under potential malicious attacks is largely neglected.To fill this gap,we employ the game theory to study the characteristics of channel interactions from both the micro and macro perspectives under the situation of channel depletion attacks.Our study is progressive,as we conduct the game-theoretic analysis of node behavioral characteristics from individuals to the whole population of PCN.Our analysis is complementary,since we utilize not only the classic game theory with the complete rationality assumption,but also the evolutionary game theory considering the limited rationality of players to portray the evolution of PCN.The results of numerous simulation experiments verify the effectiveness of our analysis.
基金supported by the National Natural Science Foundation of China under Grant Nos.61872193,61872191,and 62072254the Postgraduate Research and Practice Innovation Program of Jiangsu Province of China under Grant No.KYCX20_0762.
文摘Payment Channel Network(PCN)provides the off-chain settlement of transactions.It is one of the most promising solutions to solve the scalability issue of the blockchain.Many routing techniques in PCN have been proposed.However,both incentive attack and privacy protection have not been considered in existing studies.In this paper,we present an auction-based system model for PCN routing using the Laplace differential privacy mechanism.We formulate the cost optimization problem to minimize the path cost under the constraints of the Hashed Time-Lock Contract(HTLC)tolerance and the channel capacity.We propose an approximation algorithm to find the top K shortest paths constrained by the HTLC tolerance and the channel capacity,i.e.,top K-restricted shortest paths.Besides,we design the probability comparison function to find the path with the largest probability of having the lowest path cost among the top K-restricted shortest paths as the final path.Moreover,we apply the binary search to calculate the transaction fee of each user.Through both theoretical analysis and extensive simulations,we demonstrate that the proposed routing mechanism can guarantee the truthfulness and individual rationality with the probabilities of 1/2 and 1/4,respectively.It can also ensure the differential privacy of the users.The experiments on the real-world datasets demonstrate that the privacy leakage of the proposed mechanism is 73.21%lower than that of the unified privacy protection mechanism with only 13.2%more path cost compared with the algorithm without privacy protection on average.
基金supported by the National Nature Science Foundation of China(NSFC)under grant No.61771194supported by Key Program of Beijing Municipal Natural Science Foundation with No.17L20052
文摘In this work,a frame work for time-varying channel modeling and simulation is proposed by using neural network(NN)to overcome the shortcomings in geometry based stochastic model(GBSM)and simulation approach.Two NN models are developed for modeling of path loss together with shadow fading(SF)and joint small scale channel parameters.The NN models can predict path loss plus SF and small scale channel parameters accurately compared with measurement at 26 GHz performed in an outdoor microcell.The time-varying path loss and small scale channel parameters generated by the NN models are proposed to replace the empirical path loss and channel parameter random numbers in GBSM-based framework to playback the measured channel and match with its environment.Moreover,the sparse feature of clusters,delay and angular spread,channel capacity are investigated by a virtual array measurement at 28 GHz in a large waiting hall.
基金supported by National Key Basic Research Program of China(973 program) under Grant No. 2007CB307101National Natural Science Foundation of China under Grant No.60833002,No.60802016,No.60972010+1 种基金Next Generation Internet of China under Grant No.CNGI-0903-05the Fundamental Research Funds for the Central Universities under Grant No.2009YJS011
文摘Wireless sensor networks are suffering from serious frequency interference.In this paper,we propose a channel assignment algorithm based on graph theory in wireless sensor networks.We first model the conflict infection graph for channel assignment with the goal of global optimization minimizing the total interferences in wireless sensor networks.The channel assignment problem is equivalent to the generalized graph-coloring problem which is a NP-complete problem.We further present a meta-heuristic Wireless Sensor Network Parallel Tabu Search(WSN-PTS) algorithm,which can optimize global networks with small numbers of iterations.The results from a simulation experiment reveal that the novel algorithm can effectively solve the channel assignment problem.
基金one of the stage results of the Science and Technology Innovation Project (CI2021A00413) of the China Academy of Traditional Chinese Medicine。
文摘Along with the surge of unearthed medical literature and cultural relics in recent years,a network of channels in the system of medical conduit vessels(meridians) during the early Western Han dynasty has become much clearer gradually.In it,the increasing number of channel branches,network vessels and needle insertion holes(acupoints) is an important feature of the development of channel medicine during the Western Han dynasty.This is not only a reflection of the expanding requirements of the theoretical system of the main trunk channels and other vessels,but also an inevitable result of the continuous enrichment and accumulation of clinical experience.This article integrates the information about channel branches,network vessels,inscriptions,dots and further relics on the Tianhui(天回) Lacquered Meridian Figurine to compare the unearthed literature of the channel genre with the transmitted classical literature about acupuncture.The “Heart-Regulated Channel” in Medical Manuscripts on Bamboo Slips from Tianhui(《天回医简》) serves as an example to explain the occurrence,development and changes of the channel branches and network vessels in the early system of medical channels.
文摘Employing multiple channels in wireless multihop networks is regarded as an effective approach to increas-ing network capacity. This paper presents a centralized quasi-static channel assignment for multi-radio multi-channel Wireless Mesh Networks (WMNs). The proposed channel assignment can efficiently utilize multiple channels with only 2 radios equipped on each mesh router. In the scheme, the network end-to-end traffics are first modeled by probing data at wireless access points, and then the traffic load between each pair of neighboring routers is further estimated using an interference-aware estimation algorithm. Having knowledge of the expected link load, the scheme assigns channels to each radio with the objective of mini-mizing network interference, which as a result greatly improves network capacity. The performance evalua-tion shows that the proposed scheme is highly responsive to varying traffic conditions, and the network per-formance under the channel assignment significantly outperforms the single-radio IEEE 802.11 network as well as the 2-radio WMN with static 2 channels.
基金supported by the Natural Science Foundation of Shandong Province of China(Grant No.ZR2012AM013)
文摘We numerically study the effect of the channel noise on the spiking synchronization of a scale-free Hodgkin-Huxley neuron network with time delays. It is found that the time delay can induce synchronization transitions at an intermediate and proper channel noise intensity, and the synchronization transitions become strongest when the channel noise intensity is optimal. The neurons can also exhibit synchronization transitions as the channel noise intensity is varied, and this phenomenon is enhanced at around the time delays that can induce the synchronization transitions. It is also found that the synchronization transitions induced by the channel noise are dependent on the coupling strength and the network average degree, and there is an optimal coupling strength or network average degree with which the synchronization transitions become strongest. These results show that by inducing synchronization transitions, the channel noise has a big regulation effect on the synchronization of the neuronal network. These findings could find potential implications for the information transmission in neural systems.
基金Project supported by the National Natural Science Foundation of China(Grant No.61403336)the Natural Science Foundation of Hebei Province,China(Grant Nos.F2015203342 and F2015203291)the Independent Research Project Topics B Category for Young Teacher of Yanshan University,China(Grant No.15LGB007)
文摘In a wireless sensor network （WSN）, the energy of nodes is limited and cannot be charged. Hence, it is necessary to reduce energy consumption. Both the transmission power of nodes and the interference among nodes influence energy consumption. In this paper, we design a power control and channel allocation game model with low energy consumption （PCCAGM）. This model contains transmission power, node interference, and residual energy. Besides, the interaction between power and channel is considered. The Nash equilibrium has been proved to exist. Based on this model, a power control and channel allocation optimization algorithm with low energy consumption （PCCAA） is proposed. Theoretical analysis shows that PCCAA can converge to the Pareto Optimal. Simulation results demonstrate that this algorithm can reduce transmission power and interference effectively. Therefore, this algorithm can reduce energy consumption and prolong the network lifetime.
文摘In this paper pilot based channel estimation is being considered for broadband power line communication (BPLC) networks witch used orthogonal frequency division multiplexing (OFDM) in order to transmit high rate data. To estimate channel in time or frequency some pilot must be used. Number of these pilots and deployment of them is very important for proper estimation in different channel with varying time and frequency. Carrier sense multiple access (CSMA) and hybrid multiple access protocol are taken into consideration in MAC sub-layer. Multilayered perceptions neural network with backpropagation (BP) learning channel estimator algorithm with different pilot deployment compare to classic algorithm in for channel estimating. Simulation results show the proposed neural network estimation decreases bit error rate and therefore network throughput increases.
文摘Network Coding (NC) is confirmed to be power and bandwidth efficient technique, because of the less number of transmitted packets over the network. Wireless Sensor Network (WSN) is usually power limited network application, and in many scenarios it is power and bandwidth limited application. The proposed scenario in this paper applies the advantages of NC over WSN to obtain such power and bandwidth efficient WSN. To take the advantages of NC over the one of the most needed applications i.e., WSN, we come up to what this paper is discussing. We consider a WSN (or its cluster) that consists of M nodes that transmit equal-length information packets to a common destination node D over wireless Rayleigh block-fading channel where the instantaneous SNR is assumed to be constant over a single packet transmission period. Finite-State packet level Markov chain (FSMC) model is applied to give the channel more practical aspect. The simulation results showed that applying NC over the WSN cluster improved the channel bandwidth significantly by decreasing the number of the Automatic Repeat Request (ARQ), resulting in improving the power consumption significantly. The results are collected for different transmission distances to evaluate the behavior to the proposed scenario with regard to the bath losses effect.
基金supported in part by the National High Technology Research and Development Program of China(Grant No.2014AA01A707)the Beijing Natural Science Foundation(Grant No.4131003)+1 种基金the Specialized Research Fund for the Doctoral Program of Higher Education (SRFDP)(Grant No.20120005140002)the Key Program of Science and Technology Development Project of Beijing Municipal Education Commission of China (KZ201511232036)
文摘Relay in full-duplex(FD) mode can achieve higher spectrum efficiency than that in half-duplex mode,while it is crucial to suppress relay self-interference to ensure transmission quality which requires instantaneous channel state information(CSI). In this paper,the channel estimation issue in FD amplify-andforward relay networks is considered,where the training-based estimation technique is adopted. Firstly,the least square(LS) estimation is implemented to obtain composite channel coefficients of source-relay-destination(SRD) channel and relay loop-interference(LI) channel in order to assist destination in performing data detection. Secondly,both LS and maximum likelihood estimation methods are utilized to perform individual channel estimation aiming at supporting successive interference cancelation at destination. Finally,simulation results demonstrate the effectiveness of both composite and individual channel estimation,and the presented ML method can achieve lower MSEs than LS solution.
文摘Network coding (NC), introduced at the turn of the century, enables nodes in a network to combine data algebraically before either sending or forwarding them. Random network coding has gained popularity over the years by combining the received packet randomly before forwarding them, resulting in a complex Jordan Gaussian Elimination (JGE) decoding process. The effectiveness of random NC is through cooperation among nodes. In this paper, we propose a simple, low-complexity cooperative protocol that exploits NC in a deterministic manner resulting in improved diversity, data rate, and less complex JGE decoding process. The proposed system is applied over a lossy wireless network. The scenario under investigation is as follows: M users must send their information to a common destination D and to exchange the information between each others, over erasure channels;typically the channels between the users and the destination are worse than the channels between users. It is possible to significantly reduce the traffic among users and destination, achieving significant bandwidth savings, by combining packets from different users in simple, deterministic ways without resorting to extensive header information before being forwarded to the destination and the M users. The key problem we try to address is how to efficiently combine the packets at each user while exploiting user cooperation and the probability of successfully recovering information from all users at D with k < 2M unique linear equations, accounting for the fact that the remaining packets will be lost in the network and there are two transmission stages. Simulation results show the behaviour for two and three transmission stages. Our results show that applying NC protocols in two or three stages decreases the traffic significantly, beside the fact that the proposed protocols enable the system to retrieve the lost packets rather than asking for ARQ, resulting in improved data flow, and less power consumption. In fact, in some protocols the ARQ dropped from the rate 10ˉ<sup>1</sup> to 10ˉ<sup>4</sup>, because of the proposed combining algorithm that enables the nodes to generate additional unique linear equations to broadcast rather than repeating the same ones via ARQ. Moreover, the number of the transmitted packets in each cooperative stage dropped from M (M - 1) to just M packets, resulting to 2 M packets instead 2 (M<sup>2</sup> - 1) when three stages of transmission system are used instead of one stage (two cooperative stages).
基金the National Natural Science Foundation of China(No.61179002)the National Defence Foundation of China(No.2012JY002-260)
文摘While all-optical networks become more and more popular as the basis of the next generation Internet(NGI)infrastructure,such networks raise many critical security issues.High power inter-channel crosstalk attack is one of the security issues which have negative effect on information security in optical networks.Optical fiber in optical networks has some nonlinear characteristics,such as self phase modulation(SPM),cross phase modulation(XPM),four-wave mixing(FWM)and stimulated Raman scattering(SRS).They can be used to implement high power inter-channel crosstalk attack by malicious attackers.The mechanism of high power inter-channel crosstalk attack is analyzed.When an attack occurs,attack signal power and fiber nonlinear refractive index are the main factors which affect quality of legitimate signals.The effect of high power inter-channel crosstalk attack on quality of legitimate signals is investigated by building simulation system in VPI software.The results show that interchannel crosstalk caused by high power attack signal leads to quality deterioration of legitimate signals propagated in the same fiber.The higher the power of attack signal is,the greater the fiber nonlinear refractive index is.The closer the channel spacing away from the attack signal is,the more seriously the legitimate signals are affected by attack.We also find that when attack position and power of attack signal are constant,attack signal cannot infinitely spread,while its attack ability shows a fading trend with the extension of propagation distance.
文摘The algorithm for VLSI channel routing using Hopfield neural model is discussed inthis paper.The basic methods of mapping VLSI channel routing problem to Hopfield neural net-work,constructing energy function,setting initial neural status,and selecting various parametersare proposed.Finally,some experimental results are given.
文摘Despite extensive research, timing channels (TCs) are still known as a principal category of threats that aim to leak and transmit information by perturbing the timing or ordering of events. Existing TC detection approaches use either signature-based approaches to detect known TCs or anomaly-based approach by modeling the legitimate network traffic in order to detect unknown TCs. Un-fortunately, in a software-defined networking (SDN) environment, most existing TC detection approaches would fail due to factors such as volatile network traffic, imprecise timekeeping mechanisms, and dynamic network topology. Furthermore, stealthy TCs can be designed to mimic the legitimate traffic pattern and thus evade anomalous TC detection. In this paper, we overcome the above challenges by presenting a novel framework that harnesses the advantages of elastic re-sources in the cloud. In particular, our framework dynamically configures SDN to enable/disable differential analysis against outbound network flows of different virtual machines (VMs). Our framework is tightly coupled with a new metric that first decomposes the timing data of network flows into a number of using the discrete wavelet-based multi-resolution transform (DWMT). It then applies the Kullback-Leibler divergence (KLD) to measure the variance among flow pairs. The appealing feature of our approach is that, compared with the existing anomaly detection approaches, it can detect most existing and some new stealthy TCs without legitimate traffic for modeling, even with the presence of noise and imprecise timekeeping mechanism in an SDN virtual environment. We implement our framework as a prototype system, OBSERVER, which can be dynamically deployed in an SDN environment. Empirical evaluation shows that our approach can efficiently detect TCs with a higher detection rate, lower latency, and negligible performance overhead compared to existing approaches.
