The Belt and Road global navigation satellite system(B&R GNSS)network is the first large-scale deployment of Chinese GNSS equipment in a seismic system.Prior to this,there have been few systematic assessments of t...The Belt and Road global navigation satellite system(B&R GNSS)network is the first large-scale deployment of Chinese GNSS equipment in a seismic system.Prior to this,there have been few systematic assessments of the data quality of Chinese GNSS equipment.In this study,data from four representative GNSS sites in different regions of China were analyzed using the G-Nut/Anubis software package.Four main indicators(data integrity rate,data validity ratio,multi-path error,and cycle slip ratio)used to systematically analyze data quality,while evaluating the seismic monitoring capabilities of the network based on earthquake magnitudes estimated from high-frequency GNSS data are evaluated by estimating magnitude based on highfrequency GNSS data.The results indicate that the quality of the data produced by the three types of Chinese receivers used in the network meets the needs of earthquake monitoring and the new seismic industry standards,which provide a reference for the selection of equipment for future new projects.After the B&R GNSS network was established,the seismic monitoring capability for earthquakes with magnitudes greater than M_(W)6.5 in most parts of the Sichuan-Yunnan region improved by approximately 20%.In key areas such as the Sichuan-Yunnan Rhomboid Block,the monitoring capability increased by more than 25%,which has greatly improved the effectiveness of regional comprehensive earthquake management.展开更多
The seismological observation system in China has experienced rapid development over the Tenth Five-year Plan period. China Earthquake Administration (CEA) has completed the establishment of China digital seismologica...The seismological observation system in China has experienced rapid development over the Tenth Five-year Plan period. China Earthquake Administration (CEA) has completed the establishment of China digital seismological observation network. CEA has accomplished analog-to-digital conversion of the existing seismological observation systems and set up a number of new digital seismic stations. This indicates full digitization of seismological ob-servation in China. This paper presents an overview of the scale,layout principle and major functions of the up-dated national digital seismograph network,regional digital seismograph network,and digital seismograph net-work for volcano monitoring and mobile digital seismograph networks in China.展开更多
逻辑回归是一种广泛应用于现实分类任务的机器学习模型。随着数据孤岛问题的涌现,如何针对多参与主体非贯通数据联合构建逻辑回归模型成为一个关键问题。纵向联邦学习可实现数据明文不暴露前提下多主体跨样本特征的联合机器学习模型训...逻辑回归是一种广泛应用于现实分类任务的机器学习模型。随着数据孤岛问题的涌现,如何针对多参与主体非贯通数据联合构建逻辑回归模型成为一个关键问题。纵向联邦学习可实现数据明文不暴露前提下多主体跨样本特征的联合机器学习模型训练。然而,现有纵向联邦逻辑回归方法主要基于同态加密技术,具有计算和通信开销大的短板。针对逻辑回归模型,研究安全高效的纵向联邦学习算法,目标实现数据隐私保护和模型学习效率的较优权衡。具体地,基于秘密共享提出了一种面向逻辑回归模型的高效率纵向联邦学习算法(Vertical Federated Logistic Regression algorithm based on Secret Sharing, VFLR-SS),通过将跨域分析过程中的中间数据随机分解为多个秘密份额进行交互从而实现隐私保护,同时避免了同态加密引发的计算和通信开销。对VFLR-SS的安全性进行了分析,并基于真实数据对算法进行了验证。实验结果表明VFLR-SS可实现与集中式逻辑回归算法可比的效用和性能,大幅降低了传统同态加密方法中的计算及通信开销。展开更多
Passive worms can passively propagate through embedding themselves into some sharing files, which can result in significant damage to unstructured P2P networks. To study the passive worm behaviors, this paper firstly ...Passive worms can passively propagate through embedding themselves into some sharing files, which can result in significant damage to unstructured P2P networks. To study the passive worm behaviors, this paper firstly analyzes and obtains the average delay for all peers in the whole transmitting process due to the limitation of network throughput, and then proposes a mathematical model for the propagation of passive worms over the unstructured P2P networks. The model mainly takes the effect of the network throughput into account, and applies a new healthy files dissemination-based defense strategy according to the file popularity which follows the Zipf distribution. The simulation results show that the propagation of passive worms is mainly governed by the number of hops, initially infected files and uninfected files. The larger the number of hops, the more rapidly the passive worms propagate. If the number of the initially infected files is increased by the attackers, the propagation speed of passive worms increases obviously. A larger size of the uninfected file results in a better attack performance. However, the number of files generated by passive worms is not an important factor governing the propagation of passive worms. The effectiveness of healthy files dissemination strategy is verified. This model can provide a guideline in the control of unstructured P2P networks as well as passive worm defense.展开更多
China and its adjacent regions are heavily affected by earthquake disasters,which has led to strong demand and vigorous development of the Chinese Seismic Network(CSN).Since 2004,China Earthquake Networks Center(CENC)...China and its adjacent regions are heavily affected by earthquake disasters,which has led to strong demand and vigorous development of the Chinese Seismic Network(CSN).Since 2004,China Earthquake Networks Center(CENC)has been authorized by China Earthquake Administration(CEA)to take charge of CSN management,mainly observing product output and quality control.展开更多
The earthquake real-time monitoring system of the Chinese National Digital Seismic Network has been in operation since"the Ninth Five-year Plan"period,and the stability of the system has been well tested.In ...The earthquake real-time monitoring system of the Chinese National Digital Seismic Network has been in operation since"the Ninth Five-year Plan"period,and the stability of the system has been well tested.In recent years,with the continuous improvement of monitoring technology and increase of public demands,the original real-time monitoring system needs to be upgraded and improved in terms of timeliness,stability,accuracy and ease of operation.Therefore,by accessing a total of more than 1,000 seismic stations,reducing the seismic trigger threshold of the monitoring system,eliminating the false trigger stations and optimizing the seismic waveform display interface,the current earthquake monitoring demands can be satisfied on the basis of ensuring the stable operation of the system.展开更多
Network security situation is a hot research topic in the field of network security. Whole situation awareness includes the current situation evaluation and the future situation prediction. However, the now-existing r...Network security situation is a hot research topic in the field of network security. Whole situation awareness includes the current situation evaluation and the future situation prediction. However, the now-existing research focuses on the current situation evaluation, and seldom discusses the future prediction. Based on the historical research, an improved grey Verhulst model is put forward to predict the future situation. Aiming at the shortages in the prediction based on traditional Verhulst model, the adaptive grey parameters and equal- dimensions grey filling methods are proposed to improve the precision. The simulation results prove that the scheme is efficient and applicable.展开更多
With the rapid development of mechanical equipment, the mechanical health monitoring field has entered the era of big data. However, the method of manual feature extraction has the disadvantages of low efficiency and ...With the rapid development of mechanical equipment, the mechanical health monitoring field has entered the era of big data. However, the method of manual feature extraction has the disadvantages of low efficiency and poor accuracy, when handling big data. In this study, the research object was the asynchronous motor in the drivetrain diagnostics simulator system. The vibration signals of different fault motors were collected. The raw signal was pretreated using short time Fourier transform （STFT） to obtain the corresponding time-frequency map. Then, the feature of the time-frequency map was adap- tively extracted by using a convolutional neural network （CNN）. The effects of the pretreatment method, and the hyper parameters of network diagnostic accuracy, were investigated experimentally. The experimental results showed that the influence of the preprocessing method is small, and that the batch-size is the main factor affecting accuracy and training efficiency. By investigating feature visualization, it was shown that, in the case of big data, the extracted CNN features can represent complex mapping relationships between signal and health status, and can also overcome the prior knowledge and engineering experience requirement for feature extraction, which is used by tra- ditional diagnosis methods. This paper proposes a new method, based on STFT and CNN, which can complete motor fault diagnosis tasks more intelligently and accurately.展开更多
The IPv4 protocol suite is vulnerable to a variety of attacks. IPv6 security is in many ways the same as IPv4 security, the basic mechanisms for transporting packets across the network stay mostly unchanged, and the u...The IPv4 protocol suite is vulnerable to a variety of attacks. IPv6 security is in many ways the same as IPv4 security, the basic mechanisms for transporting packets across the network stay mostly unchanged, and the upper-layer protocols that transport the actual application data are mostly unaffected. This paper illustrates sniffing threat against IPv4 and then compares how the threat might influence an IPv6 networks. This is prefaced by a brief overview of current practices around the design of an IPv4 Internet edge network and then followed by a review of how that IPv4 edge network needs to evolve in order to secure the addition of IPv6. As IPv6 security is a large and complex subject, and also, IPv6 network is still at the very beginning stage and has not been fully examined in fact, this paper focus on the security requirements of medium edge networks.展开更多
We study the detailed malicious code propagating process in scale-free networks with link weights that denotes traffic between two nodes. It is found that the propagating velocity reaches a peak rapidly then decays in...We study the detailed malicious code propagating process in scale-free networks with link weights that denotes traffic between two nodes. It is found that the propagating velocity reaches a peak rapidly then decays in a power-law form, which is different from the well-known result in unweighted network case. Simulation results show that the nodes with larger strength are preferential to be infected, but the hierarchical dynamics are not clearly found. The simulation results also show that larger dispersion of weight of networks leads to slower propagating, which indicates that malicious code propagates more quickly in unweighted scale-free networks than in weighted scale-free networks under the same condition. These results show that not only the topology of networks but also the link weights affect the malicious propagating process.展开更多
Most existing overlay multicast approaches refuse to consider any network layer support no matter whether it is available or not. This design principle greatly increases the complexity of the routing algorithms and ma...Most existing overlay multicast approaches refuse to consider any network layer support no matter whether it is available or not. This design principle greatly increases the complexity of the routing algorithms and makes the overlay topologies incompatible with the underlying network. To address these issues, topology-aware overlay multicast over IP multicast networks (TOMIMN) was proposed as a novel overlay multicast protocol, which exploits the cooperation between end-hosts and IP multicast routers to construct a topology-aware overlay tree. Through a little modification to protocol independent multicast sparse mode (PIM-SM), a multicast router is able to receive registration from nearby group members and redirect passing-by join requests to them. Due to the multicast router's support, TOMIMN organizes its group members into an overlay multicast tree efficiently, which matches the physical network topology well.展开更多
Distributed photovoltaic(PV)is one of the important power sources for building a new power system with new energy as the main body.The rapid development of distributed PV has brought new challenges to the operation of...Distributed photovoltaic(PV)is one of the important power sources for building a new power system with new energy as the main body.The rapid development of distributed PV has brought new challenges to the operation of distribution networks.In order to improve the absorption ability of large-scale distributed PV access to the distribution network,the AC/DC hybrid distribution network is constructed based on flexible interconnection technology,and a coordinated scheduling strategy model of hydrogen energy storage(HS)and distributed PV is established.Firstly,the mathematical model of distributed PV and HS system is established,and a comprehensive energy storage system combining seasonal hydrogen energy storage(SHS)and battery(BT)is proposed.Then,a flexible interconnected distribution network scheduling optimization model is established to minimize the total active power loss,voltage deviation and system operating cost.Finally,simulation analysis is carried out on the improved IEEE33 node,the NSGA-II algorithm is used to solve specific examples,and the optimal scheduling results of the comprehensive economy and power quality of the distribution network are obtained.Compared with the method that does not consider HS and flexible interconnection technology,the network loss and voltage deviation of this method are lower,and the total system cost can be reduced by 3.55%,which verifies the effectiveness of the proposed method.展开更多
Configuration errors are proved to be the main reasons for network interruption and anomalies.Many researchers have paid their attention to configuration analysis and provisioning,but few works focus on understanding ...Configuration errors are proved to be the main reasons for network interruption and anomalies.Many researchers have paid their attention to configuration analysis and provisioning,but few works focus on understanding the configuration evolution.In this paper,we uncover the configuration evolution of an operational IP backbone based on the weekly reports gathered from January 2006 to January 2013.We find that rate limiting and launching routes for new customers are configured most frequently.In addition,we conduct an analysis of network failures and find that link failures are the main causes for network failures.We suggest that we should configure redundant links for the links which are easy to break down.At last,according to the analysis results,we illustrate how to provide semi-automated configuration for rate limiting and adding customers.展开更多
Graphs are used in various disciplines such as telecommunication,biological networks,as well as social networks.In large-scale networks,it is challenging to detect the communities by learning the distinct properties o...Graphs are used in various disciplines such as telecommunication,biological networks,as well as social networks.In large-scale networks,it is challenging to detect the communities by learning the distinct properties of the graph.As deep learning hasmade contributions in a variety of domains,we try to use deep learning techniques to mine the knowledge from large-scale graph networks.In this paper,we aim to provide a strategy for detecting communities using deep autoencoders and obtain generic neural attention to graphs.The advantages of neural attention are widely seen in the field of NLP and computer vision,which has low computational complexity for large-scale graphs.The contributions of the paper are summarized as follows.Firstly,a transformer is utilized to downsample the first-order proximities of the graph into a latent space,which can result in the structural properties and eventually assist in detecting the communities.Secondly,the fine-tuning task is conducted by tuning variant hyperparameters cautiously,which is applied to multiple social networks(Facebook and Twitch).Furthermore,the objective function(crossentropy)is tuned by L0 regularization.Lastly,the reconstructed model forms communities that present the relationship between the groups.The proposed robust model provides good generalization and is applicable to obtaining not only the community structures in social networks but also the node classification.The proposed graph-transformer shows advanced performance on the social networks with the average NMIs of 0.67±0.04,0.198±0.02,0.228±0.02,and 0.68±0.03 on Wikipedia crocodiles,Github Developers,Twitch England,and Facebook Page-Page networks,respectively.展开更多
Software defined networking( SDN) offers programmable interface to effectively control their networks by decoupling control and data plane. The network operators utilize a centralized controller to deploy advanced net...Software defined networking( SDN) offers programmable interface to effectively control their networks by decoupling control and data plane. The network operators utilize a centralized controller to deploy advanced network management strategies. An architecture for application-aware routing which can support dynamic quality of service( Qo S) in SDN networks is proposed. The applicationaware routing as a multi-constrained optimal path( MCOP) problem is proposed,where applications are treated as Qo S flow and best-effort flows. With the SDN controller applications,it is able to dynamically lead routing decisions based on application characteristics and requirements,leading to a better overall user experience and higher utilization of network resources. The simulation results show that the improvement of application-aware routing framework on discovering appropriate routes,which can provide Qo S guarantees for a specific application in SDN networks.展开更多
A multiobjective quality of service (QoS) routing algorithm was proposed and used as the QoS-aware path selection approach in differentiated services and multi-protocol label switching (DiffServ-MPLS) networks. It sim...A multiobjective quality of service (QoS) routing algorithm was proposed and used as the QoS-aware path selection approach in differentiated services and multi-protocol label switching (DiffServ-MPLS) networks. It simultaneously optimizes multiple QoS objectives by a genetic algorithm in conjunction with concept of Pareto dominance. The simulation demonstrates that the proposed algorithm is capable of discovering a set of QoS-based near optimal paths within in a few iterations. In addition, the simulation results also show the scalability of the algorithm with increasing number of network nodes.展开更多
A distributed and adaptive framework (DAF) was proposed for provisioning quality of service (QoS) in IPv6 network. In DAF, per-flow admission control and resource reservation, in conjunction with a new IPv6 flow label...A distributed and adaptive framework (DAF) was proposed for provisioning quality of service (QoS) in IPv6 network. In DAF, per-flow admission control and resource reservation, in conjunction with a new IPv6 flow label mechanism, can be performed instantaneously in a fully distributed and independent fashion at the edge of network without hop-by-hop signaling. The flow label helps in resource reservation and packets forwarding for aggregated traffic on an edge-to-edge path basis. In addition, a bounded directional probing technique for DAF was designed to reconfigure resource reservation adaptively between every pair of edge router for aggregated traffic according to the fluctuation of its traffic load. The simulation results show that DAF provides QoS guarantees to individual flows with minimal overhead, as well as keeping the scalability characteristic like DiffServ.展开更多
基金supported by grants from the National Natural Science Foundation of China(No.42004010)the B&R Seismic Monitoring Network Project of the China Earthquake Networks Center(No.5007).
文摘The Belt and Road global navigation satellite system(B&R GNSS)network is the first large-scale deployment of Chinese GNSS equipment in a seismic system.Prior to this,there have been few systematic assessments of the data quality of Chinese GNSS equipment.In this study,data from four representative GNSS sites in different regions of China were analyzed using the G-Nut/Anubis software package.Four main indicators(data integrity rate,data validity ratio,multi-path error,and cycle slip ratio)used to systematically analyze data quality,while evaluating the seismic monitoring capabilities of the network based on earthquake magnitudes estimated from high-frequency GNSS data are evaluated by estimating magnitude based on highfrequency GNSS data.The results indicate that the quality of the data produced by the three types of Chinese receivers used in the network meets the needs of earthquake monitoring and the new seismic industry standards,which provide a reference for the selection of equipment for future new projects.After the B&R GNSS network was established,the seismic monitoring capability for earthquakes with magnitudes greater than M_(W)6.5 in most parts of the Sichuan-Yunnan region improved by approximately 20%.In key areas such as the Sichuan-Yunnan Rhomboid Block,the monitoring capability increased by more than 25%,which has greatly improved the effectiveness of regional comprehensive earthquake management.
文摘The seismological observation system in China has experienced rapid development over the Tenth Five-year Plan period. China Earthquake Administration (CEA) has completed the establishment of China digital seismological observation network. CEA has accomplished analog-to-digital conversion of the existing seismological observation systems and set up a number of new digital seismic stations. This indicates full digitization of seismological ob-servation in China. This paper presents an overview of the scale,layout principle and major functions of the up-dated national digital seismograph network,regional digital seismograph network,and digital seismograph net-work for volcano monitoring and mobile digital seismograph networks in China.
文摘逻辑回归是一种广泛应用于现实分类任务的机器学习模型。随着数据孤岛问题的涌现,如何针对多参与主体非贯通数据联合构建逻辑回归模型成为一个关键问题。纵向联邦学习可实现数据明文不暴露前提下多主体跨样本特征的联合机器学习模型训练。然而,现有纵向联邦逻辑回归方法主要基于同态加密技术,具有计算和通信开销大的短板。针对逻辑回归模型,研究安全高效的纵向联邦学习算法,目标实现数据隐私保护和模型学习效率的较优权衡。具体地,基于秘密共享提出了一种面向逻辑回归模型的高效率纵向联邦学习算法(Vertical Federated Logistic Regression algorithm based on Secret Sharing, VFLR-SS),通过将跨域分析过程中的中间数据随机分解为多个秘密份额进行交互从而实现隐私保护,同时避免了同态加密引发的计算和通信开销。对VFLR-SS的安全性进行了分析,并基于真实数据对算法进行了验证。实验结果表明VFLR-SS可实现与集中式逻辑回归算法可比的效用和性能,大幅降低了传统同态加密方法中的计算及通信开销。
基金National Natural Science Foundation of China (No.60633020 and No. 90204012)Natural Science Foundation of Hebei Province (No. F2006000177)
文摘Passive worms can passively propagate through embedding themselves into some sharing files, which can result in significant damage to unstructured P2P networks. To study the passive worm behaviors, this paper firstly analyzes and obtains the average delay for all peers in the whole transmitting process due to the limitation of network throughput, and then proposes a mathematical model for the propagation of passive worms over the unstructured P2P networks. The model mainly takes the effect of the network throughput into account, and applies a new healthy files dissemination-based defense strategy according to the file popularity which follows the Zipf distribution. The simulation results show that the propagation of passive worms is mainly governed by the number of hops, initially infected files and uninfected files. The larger the number of hops, the more rapidly the passive worms propagate. If the number of the initially infected files is increased by the attackers, the propagation speed of passive worms increases obviously. A larger size of the uninfected file results in a better attack performance. However, the number of files generated by passive worms is not an important factor governing the propagation of passive worms. The effectiveness of healthy files dissemination strategy is verified. This model can provide a guideline in the control of unstructured P2P networks as well as passive worm defense.
文摘China and its adjacent regions are heavily affected by earthquake disasters,which has led to strong demand and vigorous development of the Chinese Seismic Network(CSN).Since 2004,China Earthquake Networks Center(CENC)has been authorized by China Earthquake Administration(CEA)to take charge of CSN management,mainly observing product output and quality control.
基金the China Earthquake Network Center Seismic Network Department Daily Operation and Maintenance Funding Support(1950411001)
文摘The earthquake real-time monitoring system of the Chinese National Digital Seismic Network has been in operation since"the Ninth Five-year Plan"period,and the stability of the system has been well tested.In recent years,with the continuous improvement of monitoring technology and increase of public demands,the original real-time monitoring system needs to be upgraded and improved in terms of timeliness,stability,accuracy and ease of operation.Therefore,by accessing a total of more than 1,000 seismic stations,reducing the seismic trigger threshold of the monitoring system,eliminating the false trigger stations and optimizing the seismic waveform display interface,the current earthquake monitoring demands can be satisfied on the basis of ensuring the stable operation of the system.
基金the National Natural Science Foundation of China(No.60605019)
文摘Network security situation is a hot research topic in the field of network security. Whole situation awareness includes the current situation evaluation and the future situation prediction. However, the now-existing research focuses on the current situation evaluation, and seldom discusses the future prediction. Based on the historical research, an improved grey Verhulst model is put forward to predict the future situation. Aiming at the shortages in the prediction based on traditional Verhulst model, the adaptive grey parameters and equal- dimensions grey filling methods are proposed to improve the precision. The simulation results prove that the scheme is efficient and applicable.
基金Supported by National Natural Science Foundation of China(Grant No.51405241,51505234,51575283)
文摘With the rapid development of mechanical equipment, the mechanical health monitoring field has entered the era of big data. However, the method of manual feature extraction has the disadvantages of low efficiency and poor accuracy, when handling big data. In this study, the research object was the asynchronous motor in the drivetrain diagnostics simulator system. The vibration signals of different fault motors were collected. The raw signal was pretreated using short time Fourier transform （STFT） to obtain the corresponding time-frequency map. Then, the feature of the time-frequency map was adap- tively extracted by using a convolutional neural network （CNN）. The effects of the pretreatment method, and the hyper parameters of network diagnostic accuracy, were investigated experimentally. The experimental results showed that the influence of the preprocessing method is small, and that the batch-size is the main factor affecting accuracy and training efficiency. By investigating feature visualization, it was shown that, in the case of big data, the extracted CNN features can represent complex mapping relationships between signal and health status, and can also overcome the prior knowledge and engineering experience requirement for feature extraction, which is used by tra- ditional diagnosis methods. This paper proposes a new method, based on STFT and CNN, which can complete motor fault diagnosis tasks more intelligently and accurately.
基金Supported by the China Next GernerationInternetProgram(CNGI-04-6-2T)
文摘The IPv4 protocol suite is vulnerable to a variety of attacks. IPv6 security is in many ways the same as IPv4 security, the basic mechanisms for transporting packets across the network stay mostly unchanged, and the upper-layer protocols that transport the actual application data are mostly unaffected. This paper illustrates sniffing threat against IPv4 and then compares how the threat might influence an IPv6 networks. This is prefaced by a brief overview of current practices around the design of an IPv4 Internet edge network and then followed by a review of how that IPv4 edge network needs to evolve in order to secure the addition of IPv6. As IPv6 security is a large and complex subject, and also, IPv6 network is still at the very beginning stage and has not been fully examined in fact, this paper focus on the security requirements of medium edge networks.
基金Supported by the National Natural Science Foundation of China (90204012, 60573036) and the Natural Science Foundation of Hebei Province (F2006000177)
文摘We study the detailed malicious code propagating process in scale-free networks with link weights that denotes traffic between two nodes. It is found that the propagating velocity reaches a peak rapidly then decays in a power-law form, which is different from the well-known result in unweighted network case. Simulation results show that the nodes with larger strength are preferential to be infected, but the hierarchical dynamics are not clearly found. The simulation results also show that larger dispersion of weight of networks leads to slower propagating, which indicates that malicious code propagates more quickly in unweighted scale-free networks than in weighted scale-free networks under the same condition. These results show that not only the topology of networks but also the link weights affect the malicious propagating process.
文摘Most existing overlay multicast approaches refuse to consider any network layer support no matter whether it is available or not. This design principle greatly increases the complexity of the routing algorithms and makes the overlay topologies incompatible with the underlying network. To address these issues, topology-aware overlay multicast over IP multicast networks (TOMIMN) was proposed as a novel overlay multicast protocol, which exploits the cooperation between end-hosts and IP multicast routers to construct a topology-aware overlay tree. Through a little modification to protocol independent multicast sparse mode (PIM-SM), a multicast router is able to receive registration from nearby group members and redirect passing-by join requests to them. Due to the multicast router's support, TOMIMN organizes its group members into an overlay multicast tree efficiently, which matches the physical network topology well.
文摘Distributed photovoltaic(PV)is one of the important power sources for building a new power system with new energy as the main body.The rapid development of distributed PV has brought new challenges to the operation of distribution networks.In order to improve the absorption ability of large-scale distributed PV access to the distribution network,the AC/DC hybrid distribution network is constructed based on flexible interconnection technology,and a coordinated scheduling strategy model of hydrogen energy storage(HS)and distributed PV is established.Firstly,the mathematical model of distributed PV and HS system is established,and a comprehensive energy storage system combining seasonal hydrogen energy storage(SHS)and battery(BT)is proposed.Then,a flexible interconnected distribution network scheduling optimization model is established to minimize the total active power loss,voltage deviation and system operating cost.Finally,simulation analysis is carried out on the improved IEEE33 node,the NSGA-II algorithm is used to solve specific examples,and the optimal scheduling results of the comprehensive economy and power quality of the distribution network are obtained.Compared with the method that does not consider HS and flexible interconnection technology,the network loss and voltage deviation of this method are lower,and the total system cost can be reduced by 3.55%,which verifies the effectiveness of the proposed method.
基金supported by the National Natural Science Foundation of China under Grant Nos.61602105 and 61572123China Postdoctoral Science Foundation under Grant Nos.2016M601323+1 种基金the Fundamental Research Funds for the Central Universities Project under Grant No.N150403007CERNET Innovation Project under Grant No.NGII20160126
文摘Configuration errors are proved to be the main reasons for network interruption and anomalies.Many researchers have paid their attention to configuration analysis and provisioning,but few works focus on understanding the configuration evolution.In this paper,we uncover the configuration evolution of an operational IP backbone based on the weekly reports gathered from January 2006 to January 2013.We find that rate limiting and launching routes for new customers are configured most frequently.In addition,we conduct an analysis of network failures and find that link failures are the main causes for network failures.We suggest that we should configure redundant links for the links which are easy to break down.At last,according to the analysis results,we illustrate how to provide semi-automated configuration for rate limiting and adding customers.
基金The research is funded by the Researchers Supporting Project at King Saud University(Project#RSP-2021/305).
文摘Graphs are used in various disciplines such as telecommunication,biological networks,as well as social networks.In large-scale networks,it is challenging to detect the communities by learning the distinct properties of the graph.As deep learning hasmade contributions in a variety of domains,we try to use deep learning techniques to mine the knowledge from large-scale graph networks.In this paper,we aim to provide a strategy for detecting communities using deep autoencoders and obtain generic neural attention to graphs.The advantages of neural attention are widely seen in the field of NLP and computer vision,which has low computational complexity for large-scale graphs.The contributions of the paper are summarized as follows.Firstly,a transformer is utilized to downsample the first-order proximities of the graph into a latent space,which can result in the structural properties and eventually assist in detecting the communities.Secondly,the fine-tuning task is conducted by tuning variant hyperparameters cautiously,which is applied to multiple social networks(Facebook and Twitch).Furthermore,the objective function(crossentropy)is tuned by L0 regularization.Lastly,the reconstructed model forms communities that present the relationship between the groups.The proposed robust model provides good generalization and is applicable to obtaining not only the community structures in social networks but also the node classification.The proposed graph-transformer shows advanced performance on the social networks with the average NMIs of 0.67±0.04,0.198±0.02,0.228±0.02,and 0.68±0.03 on Wikipedia crocodiles,Github Developers,Twitch England,and Facebook Page-Page networks,respectively.
基金Supported by the National Basic Research Program of China(No.2012CB315803)the Around Five Top Priorities of One-Three-Five Strategic Planning,CNIC(No.CNIC PY 1401)Chinese Academy of Sciences,and the Knowledge Innovation Program of the Chinese Academy of Sciences(No.CNIC_QN_1508)
文摘Software defined networking( SDN) offers programmable interface to effectively control their networks by decoupling control and data plane. The network operators utilize a centralized controller to deploy advanced network management strategies. An architecture for application-aware routing which can support dynamic quality of service( Qo S) in SDN networks is proposed. The applicationaware routing as a multi-constrained optimal path( MCOP) problem is proposed,where applications are treated as Qo S flow and best-effort flows. With the SDN controller applications,it is able to dynamically lead routing decisions based on application characteristics and requirements,leading to a better overall user experience and higher utilization of network resources. The simulation results show that the improvement of application-aware routing framework on discovering appropriate routes,which can provide Qo S guarantees for a specific application in SDN networks.
文摘A multiobjective quality of service (QoS) routing algorithm was proposed and used as the QoS-aware path selection approach in differentiated services and multi-protocol label switching (DiffServ-MPLS) networks. It simultaneously optimizes multiple QoS objectives by a genetic algorithm in conjunction with concept of Pareto dominance. The simulation demonstrates that the proposed algorithm is capable of discovering a set of QoS-based near optimal paths within in a few iterations. In addition, the simulation results also show the scalability of the algorithm with increasing number of network nodes.
文摘A distributed and adaptive framework (DAF) was proposed for provisioning quality of service (QoS) in IPv6 network. In DAF, per-flow admission control and resource reservation, in conjunction with a new IPv6 flow label mechanism, can be performed instantaneously in a fully distributed and independent fashion at the edge of network without hop-by-hop signaling. The flow label helps in resource reservation and packets forwarding for aggregated traffic on an edge-to-edge path basis. In addition, a bounded directional probing technique for DAF was designed to reconfigure resource reservation adaptively between every pair of edge router for aggregated traffic according to the fluctuation of its traffic load. The simulation results show that DAF provides QoS guarantees to individual flows with minimal overhead, as well as keeping the scalability characteristic like DiffServ.
