In this paper, the idea of interest coverage is provided to form clusters in sensor network, which mean that the distance among data trends gathered by neighbor sensors is so small that, in some period, those sensors ...In this paper, the idea of interest coverage is provided to form clusters in sensor network, which mean that the distance among data trends gathered by neighbor sensors is so small that, in some period, those sensors can be clustered, and certain sensor can be used to replace the cluster to form the virtual sensor network topology. In detail, the Jensen-Shannon Divergence (JSD) is used to characterize the distance among different distributions which represent the data trend of sensors. Then, based on JSD, a hierarchical clustering algorithm is provided to form the virtual sensor network topology. Simulation shows that the proposed approach gains more than 50% energy saving than Sta- tistical Aggregation Methods (SAM) which transmitted data gathered by sensor only when the differ- ence among data exceed certain threshold.展开更多
Magnetic field design is essential for the operation of Hall thrusters.This study focuses on utilizing a genetic algorithm to optimize the magnetic field configuration of SPT70.A 2D hybrid PIC-DSMC and channel-wall er...Magnetic field design is essential for the operation of Hall thrusters.This study focuses on utilizing a genetic algorithm to optimize the magnetic field configuration of SPT70.A 2D hybrid PIC-DSMC and channel-wall erosion model are employed to analyze the plume divergence angle and wall erosion rate,while a Farady probe measurement and laser profilometry system are set up to verify the simulation results.The results demonstrate that the genetic algorithm contributes to reducing the divergence angle of the thruster plumes and alleviating the impact of high-energy particles on the discharge channel wall,reducing the erosion by 5.5%and 2.7%,respectively.Further analysis indicates that the change from a divergent magnetic field to a convergent magnetic field,combined with the upstream shift of the ionization region,contributes to the improving the operation of the Hall thruster.展开更多
In Underwater Acoustic Sensor Network(UASN),routing and propagation delay is affected in each node by various water column environmental factors such as temperature,salinity,depth,gases,divergent and rotational wind.H...In Underwater Acoustic Sensor Network(UASN),routing and propagation delay is affected in each node by various water column environmental factors such as temperature,salinity,depth,gases,divergent and rotational wind.High sound velocity increases the transmission rate of the packets and the high dissolved gases in the water increases the sound velocity.High dissolved gases and sound velocity environment in the water column provides high transmission rates among UASN nodes.In this paper,the Modified Mackenzie Sound equation calculates the sound velocity in each node for energy-efficient routing.Golden Ratio Optimization Method(GROM)and Gaussian Process Regression(GPR)predicts propagation delay of each node in UASN using temperature,salinity,depth,dissolved gases dataset.Dissolved gases,rotational and divergent winds,and stress plays a major problem in UASN,which increases propagation delay and energy consumption.Predicted values from GPR and GROM leads to node selection and Corona Virus Optimization Algorithm(CVOA)routing is performed on the selected nodes.The proposed GPR-CVOA and GROM-CVOA algorithm solves the problem of propagation delay and consumes less energy in nodes,based on appropriate tolerant delays in transmitting packets among nodes during high rotational and divergent winds.From simulation results,CVOA Algorithm performs better than traditional DF and LION algorithms.展开更多
Internet services and web-based applications play pivotal roles in various sensitive domains, encompassing e-commerce, e-learning, e-healthcare, and e-payment. However, safeguarding these services poses a significant ...Internet services and web-based applications play pivotal roles in various sensitive domains, encompassing e-commerce, e-learning, e-healthcare, and e-payment. However, safeguarding these services poses a significant challenge, as the need for robust security measures becomes increasingly imperative. This paper presented an innovative method based on differential analyses to detect abrupt changes in network traffic characteristics. The core concept revolves around identifying abrupt alterations in certain characteristics such as input/output volume, the number of TCP connections, or DNS queries—within the analyzed traffic. Initially, the traffic is segmented into distinct sequences of slices, followed by quantifying specific characteristics for each slice. Subsequently, the distance between successive values of these measured characteristics is computed and clustered to detect sudden changes. To accomplish its objectives, the approach combined several techniques, including propositional logic, distance metrics (e.g., Kullback-Leibler Divergence), and clustering algorithms (e.g., K-means). When applied to two distinct datasets, the proposed approach demonstrates exceptional performance, achieving detection rates of up to 100%.展开更多
超宽带(Ultra Wide Band,UWB)室内定位系统的定位性能主要受信号非视距(None Line Of Sight,NLOS)传播影响。为此该文提出一种基于信道统计量(Channel Statistics Information,CSI)的信道NLOS状态检测法。该方法首先在IEEE802.15.4a信...超宽带(Ultra Wide Band,UWB)室内定位系统的定位性能主要受信号非视距(None Line Of Sight,NLOS)传播影响。为此该文提出一种基于信道统计量(Channel Statistics Information,CSI)的信道NLOS状态检测法。该方法首先在IEEE802.15.4a信道模型下对均方根时延扩展和平均超量延迟的概率分布函数进行建模,作为信道标准分布。再以信道瞬时分布与标准分布间的KL散度为检验统计量做似然比检验(Likelihood Ratio Test,LRT)来鉴别信道状态。同时提出一种基于LRT的定位算法LRT-Chan算法。该算法能有效利用受NLOS污染的测距数据提高定位精度。仿真结果表明:LRT信道状态检测法在全部UWB信道中都能获得较高检测准确率;在定位锚点(Anchor Node,AN)分布不理想的NLOS环境中LRT-Chan算法也能取得较高定位精度。展开更多
基金the National Natural Science Foundation of China (No.60472067)Jiangsu Education Bureau (5KJB510091)State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications (BUPT).
文摘In this paper, the idea of interest coverage is provided to form clusters in sensor network, which mean that the distance among data trends gathered by neighbor sensors is so small that, in some period, those sensors can be clustered, and certain sensor can be used to replace the cluster to form the virtual sensor network topology. In detail, the Jensen-Shannon Divergence (JSD) is used to characterize the distance among different distributions which represent the data trend of sensors. Then, based on JSD, a hierarchical clustering algorithm is provided to form the virtual sensor network topology. Simulation shows that the proposed approach gains more than 50% energy saving than Sta- tistical Aggregation Methods (SAM) which transmitted data gathered by sensor only when the differ- ence among data exceed certain threshold.
基金funded by Shanghai Natural Science Foundation(No.12ZR1414700)。
文摘Magnetic field design is essential for the operation of Hall thrusters.This study focuses on utilizing a genetic algorithm to optimize the magnetic field configuration of SPT70.A 2D hybrid PIC-DSMC and channel-wall erosion model are employed to analyze the plume divergence angle and wall erosion rate,while a Farady probe measurement and laser profilometry system are set up to verify the simulation results.The results demonstrate that the genetic algorithm contributes to reducing the divergence angle of the thruster plumes and alleviating the impact of high-energy particles on the discharge channel wall,reducing the erosion by 5.5%and 2.7%,respectively.Further analysis indicates that the change from a divergent magnetic field to a convergent magnetic field,combined with the upstream shift of the ionization region,contributes to the improving the operation of the Hall thruster.
文摘In Underwater Acoustic Sensor Network(UASN),routing and propagation delay is affected in each node by various water column environmental factors such as temperature,salinity,depth,gases,divergent and rotational wind.High sound velocity increases the transmission rate of the packets and the high dissolved gases in the water increases the sound velocity.High dissolved gases and sound velocity environment in the water column provides high transmission rates among UASN nodes.In this paper,the Modified Mackenzie Sound equation calculates the sound velocity in each node for energy-efficient routing.Golden Ratio Optimization Method(GROM)and Gaussian Process Regression(GPR)predicts propagation delay of each node in UASN using temperature,salinity,depth,dissolved gases dataset.Dissolved gases,rotational and divergent winds,and stress plays a major problem in UASN,which increases propagation delay and energy consumption.Predicted values from GPR and GROM leads to node selection and Corona Virus Optimization Algorithm(CVOA)routing is performed on the selected nodes.The proposed GPR-CVOA and GROM-CVOA algorithm solves the problem of propagation delay and consumes less energy in nodes,based on appropriate tolerant delays in transmitting packets among nodes during high rotational and divergent winds.From simulation results,CVOA Algorithm performs better than traditional DF and LION algorithms.
文摘Internet services and web-based applications play pivotal roles in various sensitive domains, encompassing e-commerce, e-learning, e-healthcare, and e-payment. However, safeguarding these services poses a significant challenge, as the need for robust security measures becomes increasingly imperative. This paper presented an innovative method based on differential analyses to detect abrupt changes in network traffic characteristics. The core concept revolves around identifying abrupt alterations in certain characteristics such as input/output volume, the number of TCP connections, or DNS queries—within the analyzed traffic. Initially, the traffic is segmented into distinct sequences of slices, followed by quantifying specific characteristics for each slice. Subsequently, the distance between successive values of these measured characteristics is computed and clustered to detect sudden changes. To accomplish its objectives, the approach combined several techniques, including propositional logic, distance metrics (e.g., Kullback-Leibler Divergence), and clustering algorithms (e.g., K-means). When applied to two distinct datasets, the proposed approach demonstrates exceptional performance, achieving detection rates of up to 100%.
文摘超宽带(Ultra Wide Band,UWB)室内定位系统的定位性能主要受信号非视距(None Line Of Sight,NLOS)传播影响。为此该文提出一种基于信道统计量(Channel Statistics Information,CSI)的信道NLOS状态检测法。该方法首先在IEEE802.15.4a信道模型下对均方根时延扩展和平均超量延迟的概率分布函数进行建模,作为信道标准分布。再以信道瞬时分布与标准分布间的KL散度为检验统计量做似然比检验(Likelihood Ratio Test,LRT)来鉴别信道状态。同时提出一种基于LRT的定位算法LRT-Chan算法。该算法能有效利用受NLOS污染的测距数据提高定位精度。仿真结果表明:LRT信道状态检测法在全部UWB信道中都能获得较高检测准确率;在定位锚点(Anchor Node,AN)分布不理想的NLOS环境中LRT-Chan算法也能取得较高定位精度。
