This paper aims to find a practical way of quantitatively representing the privacy of network data. A method of quantifying the privacy of network data anonymization based on similarity distance and entropy in the sce...This paper aims to find a practical way of quantitatively representing the privacy of network data. A method of quantifying the privacy of network data anonymization based on similarity distance and entropy in the scenario involving multiparty network data sharing with Trusted Third Party (TTP) is proposed. Simulations are then conducted using network data from different sources, and show that the measurement indicators defined in this paper can adequately quantify the privacy of the network. In particular, it can indicate the effect of the auxiliary information of the adversary on privacy.展开更多
Emerging long-range industrial IoT applications(e.g.,remote patient monitoring)have increasingly higher requirements for global deterministic delay.Although many existing methods have built deterministic networks in s...Emerging long-range industrial IoT applications(e.g.,remote patient monitoring)have increasingly higher requirements for global deterministic delay.Although many existing methods have built deterministic networks in small-scale networks through centralized computing and resource reservation,they cannot be applied on a global scale.The emerging mega-constellations enable new opportunities for realizing deterministic delay globally.As one constellation(e.g.,Starlink)might be managed by a single operator(e.g.,SpaceX),packets can be routed within deterministic number of hops.Moreover,the path diversity brought by the highly symmetrical network structure in mega-constellations can help to construct a congestion free network by routing.This paper leverages these unique characteristics of mega-constellations to avoid the traditional network congestion caused by multiple inputs and single output,and to determine the routing hops,and thus realizing a global deterministic network(DETSPACE).The model based on the 2D Markov chain theoretically verifies the correctness of DETSPACE.The effectiveness of DETSPACE in different traffic load con-ditions is also verified by extensive simulations.展开更多
Software Defined Networking(SDN) provides a flexible and convenient way to support fine-grained traffic-engineering(TE). Besides, SDN also provides better Quality of Experience(QoE) for customers. However, the policy ...Software Defined Networking(SDN) provides a flexible and convenient way to support fine-grained traffic-engineering(TE). Besides, SDN also provides better Quality of Experience(QoE) for customers. However, the policy of the evolution from legacy networks to the SDNs overemphasizes the controllability of the network or TE while ignoring the customers' benefit. Standing in the customers' position, we propose an optimization scheme, named as Optimal Migration Schedule based on Customers' Benefit(OMSB), to produce an optimized migration schedule and maximize the benefit of customers. Not only the quality and quantity of paths availed by migration, but also the number of flows from the customers that can use these multi-paths are taken into consideration for the scheduling. We compare the OMSB with other six migration schemes in terms of the benefit of customers. Our results suggest that the sequence of the migration plays a vital role for customers, especially in the early stages of the network migration to the SDN.展开更多
Based on ASP.NET,a orange fruit tree fertilizer expert system software was developed.The system could simulate and decide an annual fertilization plan for young and mature trees in terms of geographical position and c...Based on ASP.NET,a orange fruit tree fertilizer expert system software was developed.The system could simulate and decide an annual fertilization plan for young and mature trees in terms of geographical position and climate.This paper introduced the design conditions,framework,production,and deployment of the system.It exhibited characters of orange specialty and was a typical online agriculture expert system.The use of the system for orange fruit management could decrease production cost,guarantee orange quality and improve economical benefit at the same time.Farmer using the system saved N input by 41-238 g/plant,P2O5 input 3-24 g/plant,and K2O input 1-36 g/plant,and got higher yield by 6-17 kg/plant.展开更多
In order to discover the main causes of elevator group accidents in edge computing environment, a multi-dimensional data model of elevator accident data is established by using data cube technology, proposing and impl...In order to discover the main causes of elevator group accidents in edge computing environment, a multi-dimensional data model of elevator accident data is established by using data cube technology, proposing and implementing a method by combining classical Apriori algorithm with the model, digging out frequent items of elevator accident data to explore the main reasons for the occurrence of elevator accidents. In addition, a collaborative edge model of elevator accidents is set to achieve data sharing, making it possible to check the detail of each cause to confirm the causes of elevator accidents. Lastly the association rules are applied to find the law of elevator Accidents.展开更多
To achieve good results in convolutional neural networks(CNN) for text classification task, term-based pooling operation in CNNs is proposed. Firstly, the convolution results of several convolution kernels are combine...To achieve good results in convolutional neural networks(CNN) for text classification task, term-based pooling operation in CNNs is proposed. Firstly, the convolution results of several convolution kernels are combined by this method, and then the results after combination are made pooling operation, three sorts of CNN models(we named TBCNN, MCT-CNN and MMCT-CNN respectively) are constructed and then corresponding algorithmic thought are detailed on this basis. Secondly, relevant experiments and analyses are respectively designed to show the effects of three key parameters(convolution kernel, combination kernel number and word embedding) on three kinds of CNN models and to further demonstrate the effect of the models proposed. The experimental results show that compared with the traditional method of text classification in CNNs, term-based pooling method is addressed that not only the availability of the way is proved, but also the performance shows good superiority.展开更多
The most significant strategic development in information technology over the past years has been ＂trusted computing＂ and trusted computers have been produced. In this paper trusted mechanisms adopted by PC is impor...The most significant strategic development in information technology over the past years has been ＂trusted computing＂ and trusted computers have been produced. In this paper trusted mechanisms adopted by PC is imported into distributed system, such as chain of trust, trusted root and so on. Based on distributed database server system （DDSS）, a novel model of trusted distributed database server system （TDDSS） is presented ultimately. In TDDSS role-based access control, two-level of logs and other technologies are adopted to ensure the trustworthiness of the system.展开更多
Current distributed parallel file systems and database systems can not satisfy the demands of data-intensive applications, such as storage capacity, access performance, reliability, scalability, and so on. Cluster-bas...Current distributed parallel file systems and database systems can not satisfy the demands of data-intensive applications, such as storage capacity, access performance, reliability, scalability, and so on. Cluster-based storage sys tems have some shortcomings, too. To solve this kind of problems, a novel PC storage cluster solution is proposed, a distributed storage system based on 3-tiered agent architecture is designed, the system reliability model based on the masterslave backup mode is built, and the system availability is analyzed with the Markov model. According to the system availability formula and the values of the system parameters, the novel system can provide higher reliability and availability to satisfy users＇ requirements,展开更多
The Deep Packet Inspection(DPI)method is a popular method that can accurately identify the flow data and its corresponding application.Currently,the DPI method is widely used in common network management systems.Howev...The Deep Packet Inspection(DPI)method is a popular method that can accurately identify the flow data and its corresponding application.Currently,the DPI method is widely used in common network management systems.However,the major limitation of DPI systems is that their signature library is mainly extracted manually,which makes it hard to efficiently obtain the signature of new applications.Hence,in this paper,we propose an automatic signature extraction mechanism using Principal Component Analysis(PCA)technology,which is able to extract the signature automatically.In the proposed method,the signatures are expressed in the form of serial consistent sequences constructed by principal components instead of normally separated substrings in the original data extracted from the traditional methods.Extensive experiments based on numerous sets of data have been carried out to evaluate the performance of the proposed scheme,and the results prove that the newly proposed method can achieve good performance in terms of accuracy and efficiency.展开更多
Fault management is crucial to pro vi de quality of service grantees for the future networks, and fault identification is an essential part of it. A novel fault identification algorithm is proposed in this paper, wh...Fault management is crucial to pro vi de quality of service grantees for the future networks, and fault identification is an essential part of it. A novel fault identification algorithm is proposed in this paper, which focuses on the anomaly detection of network traffic. Since the fault identification has been achieved using statistical information in mana gement information base, the algorithm is compatible with the existing simple ne twork management protocol framework. The network traffic time series is verified to be non-stationary. By fitting the adaptive autoregressive model, the series is transformed into a multidimensional vector. The training samples and identif iers are acquired from the network simulation. A k-nearest neighbor classif ier identifies the system faults after being trained. The experiment results are consistent with the given fault scenarios, which prove the accuracy of the algo rithm. The identification errors are discussed to illustrate that the novel faul t identification algorithm is adaptive in the fault scenarios with network traff ic change.展开更多
This paper puts forward a survivability evaluation model, SQEM （Survivability Quantitative Evaluation Model）, based on lucubrating the main method existed. Then it defines the measurement factors and parses the surv...This paper puts forward a survivability evaluation model, SQEM （Survivability Quantitative Evaluation Model）, based on lucubrating the main method existed. Then it defines the measurement factors and parses the survivability mathematically, introduces state change probability and the idea of setting the weights of survivability factors dynamically into the evaluating process of SQEM, which improved the accuracy of evaluation. An example is presented to illustrate the way SQEM works, which demonstrated the validity and feasibility of the method.展开更多
The reliability and high performance of metadata service is crucial to the store architecture. A novel design of a two-level metadata server file system （TTMFS） is presented, which behaves high reliability and perfo...The reliability and high performance of metadata service is crucial to the store architecture. A novel design of a two-level metadata server file system （TTMFS） is presented, which behaves high reliability and performance. The merits both centralized management and distributed management are considered simultaneously in our design. In this file system, the advanced-metadata server is responsible for manage directory metadata and the whole namespace. The double-metadata server is responsible for maintaining file metadata. And this paper uses the Markov return model to analyze the reliability of the two-level metadata server. The experiment data indicates that the design can provide high throughput.展开更多
Objective To detect unknown network worm at its early propagation stage. Methods On the basis of characteristics of network worm attack, the concept of failed connection flow (FCT) was defined. Based on wavelet packet...Objective To detect unknown network worm at its early propagation stage. Methods On the basis of characteristics of network worm attack, the concept of failed connection flow (FCT) was defined. Based on wavelet packet analysis of FCT time series, this method computed the energy associated with each wavelet packet of FCT time series, transformed the FCT time series into a series of energy distribution vector on frequency domain, then a trained K-nearest neighbor (KNN) classifier was applied to identify the worm. Results The experiment showed that the method could identify network worm when the worm started to scan. Compared to theoretic value, the identification error ratio was 5.69%. Conclusion The method can detect unknown network worm at its early propagation stage effectively.展开更多
The high-pressure hydrogenation heat exchanger is an impoltmlt equipment of the refinery, but it is exposed tothe problem of leakage caused by ammonium salt corrosion. Therefore, it is very important to evaluate the o...The high-pressure hydrogenation heat exchanger is an impoltmlt equipment of the refinery, but it is exposed tothe problem of leakage caused by ammonium salt corrosion. Therefore, it is very important to evaluate the operating statusof flae hydrogenation heat exchanger. To improve flae method for evaluating the operating status of hydrogenation heat ex-chmagers by using flae traditional method, flais paper proposes a new method for evaluating the operation of hydrogenationheat exchangers based on big data. To address flae noisy data common in flae industry, this paper proposes an automatednoisy interval detection algorithm. To deal with flae problem that the sensor parameters have voluminous and mtrelateddimensions, flais paper proposes a key parameter detection algorithm based on flae Pearson correlation coefficient. Finally,this paper presents a system-based health scoring algorithm based on PCA （Principal Component Analysis） to assist site op-erators in assessing the healfla of hydrogenation heat exchangers. The evaluation of flae operating status of flae hydrorefiningheat exchange device based on big data technology will help the operators to more accurately grasp the status of flae indus-trial system mad have positive guiding significance for the early warning offlae failure.展开更多
In traditional networks,enabling new network functions often needs to add new proprietary middleboxes.However,finding the space and power to accommodate these middleboxes is becoming increasingly difficult,along with ...In traditional networks,enabling new network functions often needs to add new proprietary middleboxes.However,finding the space and power to accommodate these middleboxes is becoming increasingly difficult,along with the increasing costs of energy and capital in-vestment.Due to the heterogeneous nature of hardware middleboxes,they suffer from long development and up-grading cycles and are hard to scale at peak load.展开更多
Reasonable allocation of storage and computing resources is the basis of building big data system.With the development of IoT(Internet of Things),more data will be brought.A three-layer architecture includes smart dev...Reasonable allocation of storage and computing resources is the basis of building big data system.With the development of IoT(Internet of Things),more data will be brought.A three-layer architecture includes smart devices layer,edge cloud layer and blockchain-based distributed cloud layer.Blockchain is used in IoT for building a distributed decentralize P2P architecture to deal with the secure issue while edge computing deals with increasing volume of data.Edge caching is one of the important application scenarios.In order to allocate edge cache resources reasonably,to improve the quality of service and to reduce the waste of bandwidth resources,this paper proposes a content selection algorithm of edge cache nodes.The algorithm adopts markov chain model,improves the utilization of cache space and reduces the content transmission delay.The hierarchical caching strategy is adopted and the secondary cache stores slides of contents to expand the coverage of cached content and to reduce user waiting time.Regional node cooperation is adopted to expand the cache space and to support the regional preference of cache content.Compared with the classical substitution algorithm,simulation results show that the algorithm in this paper has higher cache hit ratio and higher space utilization.展开更多
In modern data centers, power consumed by network is an observable portion of the total energy budget and thus improving the energy efficiency of data center networks （DCNs） truly matters. One effective way for this...In modern data centers, power consumed by network is an observable portion of the total energy budget and thus improving the energy efficiency of data center networks （DCNs） truly matters. One effective way for this energy efficiency is to make the size of DCNs elastic along with traffic demands by flow consolidation and bandwidth scheduling, i.e., turning off unnecessary network components to reduce the power consumption. Meanwhile, having the instinct support for data center management, software defined networking （SDN） provides a paradigm to elastically control the resources of DCNs. To achieve such power savings, most of the prior efforts just adopt simple greedy heuristic to reduce computational complexity. However, due to the inherent problem of greedy algorithm, a good-enough optimization cannot be always guaranteed. To address this problem, a modified hybrid genetic algorithm （MHGA） is employed to improve the solution＇s accuracy, and the fine-grained routing function of SDN is fully leveraged. The simulation results show that more efficient power management can be achieved than the previous studies, by increasing about 5% of network energy savings.展开更多
Routing loops can cause packet loss and long delay problems in the traditional network. Even in future networks – Software-Defined Networks, with loop-free implementation mechanism, it still suffers loop problems. In...Routing loops can cause packet loss and long delay problems in the traditional network. Even in future networks – Software-Defined Networks, with loop-free implementation mechanism, it still suffers loop problems. In this paper, we propose an architecture to solve the loop problem in SDN. Unlike the existing passive routing loop detection algorithm, this algorithm processes based on the SDN loop-free characteristic, by auditing third-party network forwarding rules’ modification requests to avoids loop generation, thus avoid the network loop problems. Testbed is built to simulate our proposed algorithm. The evaluation shows that the loop audit algorithm proposed in this paper has better performance in extra spatial utilization and smaller number of extra interactions between SDN controller and switches.展开更多
Recently,backscatter communication(BC)has been introduced as a green paradigm for Internet of Things(IoT).Meanwhile,unmanned aerial vehicles(UAVs)can serve as aerial base stations(BSs)to enhance the performance of BC ...Recently,backscatter communication(BC)has been introduced as a green paradigm for Internet of Things(IoT).Meanwhile,unmanned aerial vehicles(UAVs)can serve as aerial base stations(BSs)to enhance the performance of BC system thanks to their high mobility and flexibility.In this paper,we investigate the problem of energy efficiency(EE)for an energy-limited backscatter communication(BC)network,where backscatter devices(BDs)on the ground harvest energy from the wireless signal of a flying rotary-wing quadrotor.Specifically,we first reformulate the EE optimization problem as a Markov decision process(MDP)and then propose a deep reinforcement learning(DRL)algorithm to design the UAV trajectory with the constraints of the BD scheduling,the power reflection coefficients,the transmission power,and the fairness among BDs.Simulation results show the proposed DRL algorithm achieves close-to-optimal performance and significant EE gains compared to the benchmark schemes.展开更多
Efficient and effective data acquisition is of theoretical and practical importance in WSN applications because data measured and collected by WSN is often unreliable, such as those often accompanied by noise and erro...Efficient and effective data acquisition is of theoretical and practical importance in WSN applications because data measured and collected by WSN is often unreliable, such as those often accompanied by noise and error, missing values or inconsistent data. Motivated by fog computing, which focuses on how to effectively offload computation-intensive tasks from resource-constrained devices, this paper proposes a simple but yet effective data acquisition approach with the ability of filtering abnormal data and meeting the real-time requirement. Our method uses a cooperation mechanism by leveraging on both an architectural and algorithmic approach. Firstly, the sensor node with the limited computing resource only accomplishes detecting and marking the suspicious data using a light weight algorithm. Secondly, the cluster head evaluates suspicious data by referring to the data from the other sensor nodes in the same cluster and discard the abnormal data directly. Thirdly, the sink node fills up the discarded data with an approximate value using nearest neighbor data supplement method. Through the architecture, each node only consumes a few computational resources and distributes the heavily computing load to several nodes. Simulation results show that our data acquisition method is effective considering the real-time outlier filtering and the computing overhead.展开更多
基金supported by the National Key Basic Research Program of China (973 Program) under Grant No. 2009CB320505the Fundamental Research Funds for the Central Universities under Grant No. 2011RC0508+2 种基金the National Natural Science Foundation of China under Grant No. 61003282China Next Generation Internet Project "Research and Trial on Evolving Next Generation Network Intelligence Capability Enhancement"the National Science and Technology Major Project "Research about Architecture of Mobile Internet" under Grant No. 2011ZX03002-001-01
文摘This paper aims to find a practical way of quantitatively representing the privacy of network data. A method of quantifying the privacy of network data anonymization based on similarity distance and entropy in the scenario involving multiparty network data sharing with Trusted Third Party (TTP) is proposed. Simulations are then conducted using network data from different sources, and show that the measurement indicators defined in this paper can adequately quantify the privacy of the network. In particular, it can indicate the effect of the auxiliary information of the adversary on privacy.
基金This work is supported by National Key Research and Development Plan of China(2022YFB3105204).
文摘Emerging long-range industrial IoT applications(e.g.,remote patient monitoring)have increasingly higher requirements for global deterministic delay.Although many existing methods have built deterministic networks in small-scale networks through centralized computing and resource reservation,they cannot be applied on a global scale.The emerging mega-constellations enable new opportunities for realizing deterministic delay globally.As one constellation(e.g.,Starlink)might be managed by a single operator(e.g.,SpaceX),packets can be routed within deterministic number of hops.Moreover,the path diversity brought by the highly symmetrical network structure in mega-constellations can help to construct a congestion free network by routing.This paper leverages these unique characteristics of mega-constellations to avoid the traditional network congestion caused by multiple inputs and single output,and to determine the routing hops,and thus realizing a global deterministic network(DETSPACE).The model based on the 2D Markov chain theoretically verifies the correctness of DETSPACE.The effectiveness of DETSPACE in different traffic load con-ditions is also verified by extensive simulations.
基金supported by Joint Funds of National Natural Science Foundation of China and Xinjiang under code U1603261the Research Fund of Ministry of Education-China Mobile under Grant No. MCM20160304the Fundamental Research Funds for the Central Universities
文摘Software Defined Networking(SDN) provides a flexible and convenient way to support fine-grained traffic-engineering(TE). Besides, SDN also provides better Quality of Experience(QoE) for customers. However, the policy of the evolution from legacy networks to the SDNs overemphasizes the controllability of the network or TE while ignoring the customers' benefit. Standing in the customers' position, we propose an optimization scheme, named as Optimal Migration Schedule based on Customers' Benefit(OMSB), to produce an optimized migration schedule and maximize the benefit of customers. Not only the quality and quantity of paths availed by migration, but also the number of flows from the customers that can use these multi-paths are taken into consideration for the scheduling. We compare the OMSB with other six migration schemes in terms of the benefit of customers. Our results suggest that the sequence of the migration plays a vital role for customers, especially in the early stages of the network migration to the SDN.
基金fund by the Major Science and Technology Program (2009ZX07102-004),Chinathe IPNI (International Plant Nutrition Institute) Program,Canada (2009ZX07102-004)
文摘Based on ASP.NET,a orange fruit tree fertilizer expert system software was developed.The system could simulate and decide an annual fertilization plan for young and mature trees in terms of geographical position and climate.This paper introduced the design conditions,framework,production,and deployment of the system.It exhibited characters of orange specialty and was a typical online agriculture expert system.The use of the system for orange fruit management could decrease production cost,guarantee orange quality and improve economical benefit at the same time.Farmer using the system saved N input by 41-238 g/plant,P2O5 input 3-24 g/plant,and K2O input 1-36 g/plant,and got higher yield by 6-17 kg/plant.
文摘In order to discover the main causes of elevator group accidents in edge computing environment, a multi-dimensional data model of elevator accident data is established by using data cube technology, proposing and implementing a method by combining classical Apriori algorithm with the model, digging out frequent items of elevator accident data to explore the main reasons for the occurrence of elevator accidents. In addition, a collaborative edge model of elevator accidents is set to achieve data sharing, making it possible to check the detail of each cause to confirm the causes of elevator accidents. Lastly the association rules are applied to find the law of elevator Accidents.
文摘To achieve good results in convolutional neural networks(CNN) for text classification task, term-based pooling operation in CNNs is proposed. Firstly, the convolution results of several convolution kernels are combined by this method, and then the results after combination are made pooling operation, three sorts of CNN models(we named TBCNN, MCT-CNN and MMCT-CNN respectively) are constructed and then corresponding algorithmic thought are detailed on this basis. Secondly, relevant experiments and analyses are respectively designed to show the effects of three key parameters(convolution kernel, combination kernel number and word embedding) on three kinds of CNN models and to further demonstrate the effect of the models proposed. The experimental results show that compared with the traditional method of text classification in CNNs, term-based pooling method is addressed that not only the availability of the way is proved, but also the performance shows good superiority.
基金Supported by the Natural Science Foundation ofHebei Province (F2004000133)
文摘The most significant strategic development in information technology over the past years has been ＂trusted computing＂ and trusted computers have been produced. In this paper trusted mechanisms adopted by PC is imported into distributed system, such as chain of trust, trusted root and so on. Based on distributed database server system （DDSS）, a novel model of trusted distributed database server system （TDDSS） is presented ultimately. In TDDSS role-based access control, two-level of logs and other technologies are adopted to ensure the trustworthiness of the system.
基金Supported by the Industrialization Foundation ofHebei Province (020501)the Natural Science Foundation ofHebei University (2005Q04)
文摘Current distributed parallel file systems and database systems can not satisfy the demands of data-intensive applications, such as storage capacity, access performance, reliability, scalability, and so on. Cluster-based storage sys tems have some shortcomings, too. To solve this kind of problems, a novel PC storage cluster solution is proposed, a distributed storage system based on 3-tiered agent architecture is designed, the system reliability model based on the masterslave backup mode is built, and the system availability is analyzed with the Markov model. According to the system availability formula and the values of the system parameters, the novel system can provide higher reliability and availability to satisfy users＇ requirements,
基金supported by the National Natural Science Foundation of China under Grant No.61003282Beijing Higher Education Young Elite Teacher Project+3 种基金China Next Generation Internet(CNGI)Project"Research and Trial on Evolving Next Generation Network Intelligence Capability Enhancement(NICE)"the National Basic Research Program(973 Program)under Grant No.2009CB320-505the National Science and Technology Major Project"Research about Architecture of Mobile Internet"under Grant No.2011ZX03-002-001-01the National High Technology Research and Development Program(863 Program)under Grant No.2011AA010704
文摘The Deep Packet Inspection(DPI)method is a popular method that can accurately identify the flow data and its corresponding application.Currently,the DPI method is widely used in common network management systems.However,the major limitation of DPI systems is that their signature library is mainly extracted manually,which makes it hard to efficiently obtain the signature of new applications.Hence,in this paper,we propose an automatic signature extraction mechanism using Principal Component Analysis(PCA)technology,which is able to extract the signature automatically.In the proposed method,the signatures are expressed in the form of serial consistent sequences constructed by principal components instead of normally separated substrings in the original data extracted from the traditional methods.Extensive experiments based on numerous sets of data have been carried out to evaluate the performance of the proposed scheme,and the results prove that the newly proposed method can achieve good performance in terms of accuracy and efficiency.
文摘Fault management is crucial to pro vi de quality of service grantees for the future networks, and fault identification is an essential part of it. A novel fault identification algorithm is proposed in this paper, which focuses on the anomaly detection of network traffic. Since the fault identification has been achieved using statistical information in mana gement information base, the algorithm is compatible with the existing simple ne twork management protocol framework. The network traffic time series is verified to be non-stationary. By fitting the adaptive autoregressive model, the series is transformed into a multidimensional vector. The training samples and identif iers are acquired from the network simulation. A k-nearest neighbor classif ier identifies the system faults after being trained. The experiment results are consistent with the given fault scenarios, which prove the accuracy of the algo rithm. The identification errors are discussed to illustrate that the novel faul t identification algorithm is adaptive in the fault scenarios with network traff ic change.
基金Supported by Natural Science Fundation of HebeiProvince (F2004000133)
文摘This paper puts forward a survivability evaluation model, SQEM （Survivability Quantitative Evaluation Model）, based on lucubrating the main method existed. Then it defines the measurement factors and parses the survivability mathematically, introduces state change probability and the idea of setting the weights of survivability factors dynamically into the evaluating process of SQEM, which improved the accuracy of evaluation. An example is presented to illustrate the way SQEM works, which demonstrated the validity and feasibility of the method.
基金Supported by the Industrialized Foundation ofHebei Province (F020501)
文摘The reliability and high performance of metadata service is crucial to the store architecture. A novel design of a two-level metadata server file system （TTMFS） is presented, which behaves high reliability and performance. The merits both centralized management and distributed management are considered simultaneously in our design. In this file system, the advanced-metadata server is responsible for manage directory metadata and the whole namespace. The double-metadata server is responsible for maintaining file metadata. And this paper uses the Markov return model to analyze the reliability of the two-level metadata server. The experiment data indicates that the design can provide high throughput.
基金This work was supported by National "863" programof China (No.2003AA148010) and National Torch Project of China (No.2005EB011484) .
文摘Objective To detect unknown network worm at its early propagation stage. Methods On the basis of characteristics of network worm attack, the concept of failed connection flow (FCT) was defined. Based on wavelet packet analysis of FCT time series, this method computed the energy associated with each wavelet packet of FCT time series, transformed the FCT time series into a series of energy distribution vector on frequency domain, then a trained K-nearest neighbor (KNN) classifier was applied to identify the worm. Results The experiment showed that the method could identify network worm when the worm started to scan. Compared to theoretic value, the identification error ratio was 5.69%. Conclusion The method can detect unknown network worm at its early propagation stage effectively.
基金supported by the National Natural Science Foundation of China (U1534201)the open project of Science and Technology on Communication Networks Laboratorythe National Key Research and Development Program of China (2016QY01W0200)
文摘The high-pressure hydrogenation heat exchanger is an impoltmlt equipment of the refinery, but it is exposed tothe problem of leakage caused by ammonium salt corrosion. Therefore, it is very important to evaluate the operating statusof flae hydrogenation heat exchanger. To improve flae method for evaluating the operating status of hydrogenation heat ex-chmagers by using flae traditional method, flais paper proposes a new method for evaluating the operation of hydrogenationheat exchangers based on big data. To address flae noisy data common in flae industry, this paper proposes an automatednoisy interval detection algorithm. To deal with flae problem that the sensor parameters have voluminous and mtrelateddimensions, flais paper proposes a key parameter detection algorithm based on flae Pearson correlation coefficient. Finally,this paper presents a system-based health scoring algorithm based on PCA （Principal Component Analysis） to assist site op-erators in assessing the healfla of hydrogenation heat exchangers. The evaluation of flae operating status of flae hydrorefiningheat exchange device based on big data technology will help the operators to more accurately grasp the status of flae indus-trial system mad have positive guiding significance for the early warning offlae failure.
文摘In traditional networks,enabling new network functions often needs to add new proprietary middleboxes.However,finding the space and power to accommodate these middleboxes is becoming increasingly difficult,along with the increasing costs of energy and capital in-vestment.Due to the heterogeneous nature of hardware middleboxes,they suffer from long development and up-grading cycles and are hard to scale at peak load.
文摘Reasonable allocation of storage and computing resources is the basis of building big data system.With the development of IoT(Internet of Things),more data will be brought.A three-layer architecture includes smart devices layer,edge cloud layer and blockchain-based distributed cloud layer.Blockchain is used in IoT for building a distributed decentralize P2P architecture to deal with the secure issue while edge computing deals with increasing volume of data.Edge caching is one of the important application scenarios.In order to allocate edge cache resources reasonably,to improve the quality of service and to reduce the waste of bandwidth resources,this paper proposes a content selection algorithm of edge cache nodes.The algorithm adopts markov chain model,improves the utilization of cache space and reduces the content transmission delay.The hierarchical caching strategy is adopted and the secondary cache stores slides of contents to expand the coverage of cached content and to reduce user waiting time.Regional node cooperation is adopted to expand the cache space and to support the regional preference of cache content.Compared with the classical substitution algorithm,simulation results show that the algorithm in this paper has higher cache hit ratio and higher space utilization.
基金supported by the Research Fund of Ministry of Education-China Mobile (MCM20160304)
文摘In modern data centers, power consumed by network is an observable portion of the total energy budget and thus improving the energy efficiency of data center networks （DCNs） truly matters. One effective way for this energy efficiency is to make the size of DCNs elastic along with traffic demands by flow consolidation and bandwidth scheduling, i.e., turning off unnecessary network components to reduce the power consumption. Meanwhile, having the instinct support for data center management, software defined networking （SDN） provides a paradigm to elastically control the resources of DCNs. To achieve such power savings, most of the prior efforts just adopt simple greedy heuristic to reduce computational complexity. However, due to the inherent problem of greedy algorithm, a good-enough optimization cannot be always guaranteed. To address this problem, a modified hybrid genetic algorithm （MHGA） is employed to improve the solution＇s accuracy, and the fine-grained routing function of SDN is fully leveraged. The simulation results show that more efficient power management can be achieved than the previous studies, by increasing about 5% of network energy savings.
基金supported by the project of Ministry of science and technology special emphasis Research and Development Surveying and Mapping Cyberspace Resources (NO. 112044017001)Cernet Next Generation Internet Technology Innovation(No. NGII20170417)China Ministry of Education-CMCC Research Fund (No. MCM20170306)
文摘Routing loops can cause packet loss and long delay problems in the traditional network. Even in future networks – Software-Defined Networks, with loop-free implementation mechanism, it still suffers loop problems. In this paper, we propose an architecture to solve the loop problem in SDN. Unlike the existing passive routing loop detection algorithm, this algorithm processes based on the SDN loop-free characteristic, by auditing third-party network forwarding rules’ modification requests to avoids loop generation, thus avoid the network loop problems. Testbed is built to simulate our proposed algorithm. The evaluation shows that the loop audit algorithm proposed in this paper has better performance in extra spatial utilization and smaller number of extra interactions between SDN controller and switches.
基金the National Natural Science Foundation of China 61661021,61971191,61902214,and 61871321,in part by the Beijing Natural Science Foundation under Grant L182018,in part by the National Science and Technology Major Project of the Ministry of Science and Technology of China under Grant 2016ZX03001014-006in part by the open project of Shanghai Institute of Microsystem and Information Technology(20190910)+1 种基金in part by the Key project of Natural Science Foundation of Jiangxi Province(20202ACBL202006)in part by the open project of Key Laboratory of Wireless Sensor Network&Communication,Shanghai Institute of Microsystem and Information Technology,Chinese Academy of Sciences,865 Changning Road,Shanghai 200050 China,and in part by the Tsinghua University Initiative Scientific Research Program 2019Z08QCX19.
文摘Recently,backscatter communication(BC)has been introduced as a green paradigm for Internet of Things(IoT).Meanwhile,unmanned aerial vehicles(UAVs)can serve as aerial base stations(BSs)to enhance the performance of BC system thanks to their high mobility and flexibility.In this paper,we investigate the problem of energy efficiency(EE)for an energy-limited backscatter communication(BC)network,where backscatter devices(BDs)on the ground harvest energy from the wireless signal of a flying rotary-wing quadrotor.Specifically,we first reformulate the EE optimization problem as a Markov decision process(MDP)and then propose a deep reinforcement learning(DRL)algorithm to design the UAV trajectory with the constraints of the BD scheduling,the power reflection coefficients,the transmission power,and the fairness among BDs.Simulation results show the proposed DRL algorithm achieves close-to-optimal performance and significant EE gains compared to the benchmark schemes.
基金supported by National Natural Science Foundation of China, "Research on Accurate and Fair Service Recommendation Approach in Mobile Internet Environment", (No. 61571066)
文摘Efficient and effective data acquisition is of theoretical and practical importance in WSN applications because data measured and collected by WSN is often unreliable, such as those often accompanied by noise and error, missing values or inconsistent data. Motivated by fog computing, which focuses on how to effectively offload computation-intensive tasks from resource-constrained devices, this paper proposes a simple but yet effective data acquisition approach with the ability of filtering abnormal data and meeting the real-time requirement. Our method uses a cooperation mechanism by leveraging on both an architectural and algorithmic approach. Firstly, the sensor node with the limited computing resource only accomplishes detecting and marking the suspicious data using a light weight algorithm. Secondly, the cluster head evaluates suspicious data by referring to the data from the other sensor nodes in the same cluster and discard the abnormal data directly. Thirdly, the sink node fills up the discarded data with an approximate value using nearest neighbor data supplement method. Through the architecture, each node only consumes a few computational resources and distributes the heavily computing load to several nodes. Simulation results show that our data acquisition method is effective considering the real-time outlier filtering and the computing overhead.
