The controller is indispensable in software-defined networking(SDN).With several features,controllers monitor the network and respond promptly to dynamic changes.Their performance affects the quality-of-service(QoS)in...The controller is indispensable in software-defined networking(SDN).With several features,controllers monitor the network and respond promptly to dynamic changes.Their performance affects the quality-of-service(QoS)in SDN.Every controller supports a set of features.However,the support of the features may be more prominent in one controller.Moreover,a single controller leads to performance,single-point-of-failure(SPOF),and scalability problems.To overcome this,a controller with an optimum feature set must be available for SDN.Furthermore,a cluster of optimum feature set controllers will overcome an SPOF and improve the QoS in SDN.Herein,leveraging an analytical network process(ANP),we rank SDN controllers regarding their supporting features and create a hierarchical control plane based cluster(HCPC)of the highly ranked controller computed using the ANP,evaluating their performance for the OS3E topology.The results demonstrated in Mininet reveal that a HCPC environment with an optimum controller achieves an improved QoS.Moreover,the experimental results validated in Mininet show that our proposed approach surpasses the existing distributed controller clustering(DCC)schemes in terms of several performance metrics i.e.,delay,jitter,throughput,load balancing,scalability and CPU(central processing unit)utilization.展开更多
Earthquake rupture process generally involves several faults activities instead of a single fault A new method using both fuzzy clustering and principal component analysis makes it possible to reconstruct three dimens...Earthquake rupture process generally involves several faults activities instead of a single fault A new method using both fuzzy clustering and principal component analysis makes it possible to reconstruct three dimensional structure of involved faults in earthquake if the aftershocks around the active fault planes distribute uniformly. When seismic events are given, the optimal faults structures can be determined by our new method. Each of sub-fault planes is fully characterized by its central location, length, width, strike and dip. The resolution determines the number of fault segments needed to describe the earthquake catalog. The higher the resolution, the finer the structure of the reconstructed fault segments. The new method successfully reconstructs the fault segments using synthetic earthquake catalogs. By taking the 28 June 1992 Landers earthquake oceured in southern California as an example, the reconstructed fault segments are consistent with the faults already known on geological maps or blind faults that appeared quite frequently in longer-term catalogs.展开更多
With the advancement in geospatial data acquisition technology, large sizes of digital data are being collected for our world. These include air- and space-borne imagery, LiDAR data, sonar data, terrestrial laser-scan...With the advancement in geospatial data acquisition technology, large sizes of digital data are being collected for our world. These include air- and space-borne imagery, LiDAR data, sonar data, terrestrial laser-scanning data, etc. LiDAR sensors generate huge datasets of point of multiple returns. Because of its large size, LiDAR data has costly storage and computational requirements. In this article, a LiDAR compression method based on spatial clustering and optimal filtering is presented. The method consists of classification and spatial clustering of the study area image and creation of the optimal planes in the LiDAR dataset through first-order plane-fitting. First-order plane-fitting is equivalent to the Eigen value problem of the covariance matrix. The Eigen value of the covariance matrix represents the spatial variation along the direction of the corresponding eigenvector. The eigenvector of the minimum Eigen value is the estimated normal vector of the surface formed by the LiDAR point and its neighbors. The ratio of the minimum Eigen value and the sum of the Eigen values approximates the change of local curvature, which determines the deviation of the surface formed by a LiDAR point and its neighbors from the tangential plane formed at that neighborhood. If the minimum Eigen value is close to zero for example, then the surface consisting of the point and its neighbors is a plane. The objective of this ongoing research work is basically to develop a LiDAR compression method that can be used in the future at the data acquisition phase to help remove fake returns and redundant points.展开更多
This paper proposes a virtual router cluster system based on the separation of the control plane and the data plane from multiple perspectives,such as architecture,key technologies,scenarios and standardization.To som...This paper proposes a virtual router cluster system based on the separation of the control plane and the data plane from multiple perspectives,such as architecture,key technologies,scenarios and standardization.To some extent,the virtual cluster simplifies network topology and management,achieves automatic conFig.uration and saves the IP address.It is a kind of low-cost expansion method of aggregation equipment port density.展开更多
Using first-principles pseudo-potential plane wave method, the energetics, geometrical and electronic structures of three Al13I cluster isomers were calculated. The calculation results of the binding energy indicate A...Using first-principles pseudo-potential plane wave method, the energetics, geometrical and electronic structures of three Al13I cluster isomers were calculated. The calculation results of the binding energy indicate Al13I cluster is more stable than Al13 cluster although its electrons are not a magic number as in Alia cluster, and among Al13I cluster isomers the ＂Bridge＂ structure is the most stable, the second is the ＂Ontop＂ structure, and the worst is the ＂Hollow＂ structure. By analyzing the geometrical structures of Al13I cluster isomers, it is found that after I atom and Al13 cluster combine the geometrical structures of Al13 moieties are changed besides Al13I Hollow cluster, in which the Alia moiety is still a regular icosahedron. For Al13I Ontop cluster, the Al13 moiety has a shrinking trend to I, whereas in Al13I Bridge cluster it is distorted. Mulliken population analysis shows for the interaction of electrons between Al-I atoms in Al13I cluster not only there exists an ionic bonding but there is a covalent bonding. Part of electrons in the Alia cluster transfer to I as Al13 cluster and I atom combine. The order of the strength of covalent bonding between Al13 moiety and I in Al13I cluster isomers is Al13IBridge〉Al13IHollow〉Al13I Ontop. Further analysis of electric structures of Al13 and Al13I clusters indicates a higher stability of Al13I cluster than Al13 cluster can be attributed to the s-p hybridization of 3s and 3p electrons of Al in Al13 moiety induced by 1 doped, which leads to fewer electrons N（EF） at EF in Al13I and a larger energy gap △EH-L between HOMO and LUMO levels in Al13I cluster. The distinguish of structural stability of Al13I cluster isomers mainly originates from their different magnitudes .in decrease of N（EF） and increase of △EH-L relative to Al13 cluster. The fewest N（EF） and the largest △EH-L are responsible for the high stability of Al13I Bridge cluster.展开更多
This paper gives a mathematical approach to calculate the fractionation factor of isotopes in a general cluster (also known as?super-molecule), which composes of necessary chemical effect within three bonds outside th...This paper gives a mathematical approach to calculate the fractionation factor of isotopes in a general cluster (also known as?super-molecule), which composes of necessary chemical effect within three bonds outside the interested atom(s). The cluster might have imaginary frequencies after being optimized in quantum softwares. The approach includes the contribution of the difference, which is resulted from the substitution of heavy and light isotopes in the cluster, of vibrations of imaginary frequencies to give precise prediction of isotope fractionation factor. We call the new mathematical approximation “reduced partition function ratio in the frequency complex plane (RPFRC)”. If there is no imaginary frequency for a cluster, RPFRC?is simplified to be Urey (1947) or Bigeleisen and Mayer (1947) formula. Final results of this new algorithm are in good agreement with those in earlier studies.展开更多
基金supported by the MSIT(Ministry of Science and ICT),Korea,under the ITRC(Information Technology Research Center)support program(IITP-2020-2018-0-01431)supervised by the IITP(Institute for Information&Communications Technology Planning&Evaluation).
文摘The controller is indispensable in software-defined networking(SDN).With several features,controllers monitor the network and respond promptly to dynamic changes.Their performance affects the quality-of-service(QoS)in SDN.Every controller supports a set of features.However,the support of the features may be more prominent in one controller.Moreover,a single controller leads to performance,single-point-of-failure(SPOF),and scalability problems.To overcome this,a controller with an optimum feature set must be available for SDN.Furthermore,a cluster of optimum feature set controllers will overcome an SPOF and improve the QoS in SDN.Herein,leveraging an analytical network process(ANP),we rank SDN controllers regarding their supporting features and create a hierarchical control plane based cluster(HCPC)of the highly ranked controller computed using the ANP,evaluating their performance for the OS3E topology.The results demonstrated in Mininet reveal that a HCPC environment with an optimum controller achieves an improved QoS.Moreover,the experimental results validated in Mininet show that our proposed approach surpasses the existing distributed controller clustering(DCC)schemes in terms of several performance metrics i.e.,delay,jitter,throughput,load balancing,scalability and CPU(central processing unit)utilization.
基金the financial support of the Teachers Scientific and Research Fund of China Earthquake Administration (20090126)the Natural Science Fund of Hebei Province (A2011408006)the Fundamental Research Funds for the Central Universities (ZY20110101)
文摘Earthquake rupture process generally involves several faults activities instead of a single fault A new method using both fuzzy clustering and principal component analysis makes it possible to reconstruct three dimensional structure of involved faults in earthquake if the aftershocks around the active fault planes distribute uniformly. When seismic events are given, the optimal faults structures can be determined by our new method. Each of sub-fault planes is fully characterized by its central location, length, width, strike and dip. The resolution determines the number of fault segments needed to describe the earthquake catalog. The higher the resolution, the finer the structure of the reconstructed fault segments. The new method successfully reconstructs the fault segments using synthetic earthquake catalogs. By taking the 28 June 1992 Landers earthquake oceured in southern California as an example, the reconstructed fault segments are consistent with the faults already known on geological maps or blind faults that appeared quite frequently in longer-term catalogs.
文摘With the advancement in geospatial data acquisition technology, large sizes of digital data are being collected for our world. These include air- and space-borne imagery, LiDAR data, sonar data, terrestrial laser-scanning data, etc. LiDAR sensors generate huge datasets of point of multiple returns. Because of its large size, LiDAR data has costly storage and computational requirements. In this article, a LiDAR compression method based on spatial clustering and optimal filtering is presented. The method consists of classification and spatial clustering of the study area image and creation of the optimal planes in the LiDAR dataset through first-order plane-fitting. First-order plane-fitting is equivalent to the Eigen value problem of the covariance matrix. The Eigen value of the covariance matrix represents the spatial variation along the direction of the corresponding eigenvector. The eigenvector of the minimum Eigen value is the estimated normal vector of the surface formed by the LiDAR point and its neighbors. The ratio of the minimum Eigen value and the sum of the Eigen values approximates the change of local curvature, which determines the deviation of the surface formed by a LiDAR point and its neighbors from the tangential plane formed at that neighborhood. If the minimum Eigen value is close to zero for example, then the surface consisting of the point and its neighbors is a plane. The objective of this ongoing research work is basically to develop a LiDAR compression method that can be used in the future at the data acquisition phase to help remove fake returns and redundant points.
基金supported by the Collaboration Research on Key Techniques of Future Network between China,Japan and Korea(2010DFB13470)~~
文摘This paper proposes a virtual router cluster system based on the separation of the control plane and the data plane from multiple perspectives,such as architecture,key technologies,scenarios and standardization.To some extent,the virtual cluster simplifies network topology and management,achieves automatic conFig.uration and saves the IP address.It is a kind of low-cost expansion method of aggregation equipment port density.
基金This work was supported by the Science & Technology Major Programs of Ministry of Education of China (No. 101139)
文摘Using first-principles pseudo-potential plane wave method, the energetics, geometrical and electronic structures of three Al13I cluster isomers were calculated. The calculation results of the binding energy indicate Al13I cluster is more stable than Al13 cluster although its electrons are not a magic number as in Alia cluster, and among Al13I cluster isomers the ＂Bridge＂ structure is the most stable, the second is the ＂Ontop＂ structure, and the worst is the ＂Hollow＂ structure. By analyzing the geometrical structures of Al13I cluster isomers, it is found that after I atom and Al13 cluster combine the geometrical structures of Al13 moieties are changed besides Al13I Hollow cluster, in which the Alia moiety is still a regular icosahedron. For Al13I Ontop cluster, the Al13 moiety has a shrinking trend to I, whereas in Al13I Bridge cluster it is distorted. Mulliken population analysis shows for the interaction of electrons between Al-I atoms in Al13I cluster not only there exists an ionic bonding but there is a covalent bonding. Part of electrons in the Alia cluster transfer to I as Al13 cluster and I atom combine. The order of the strength of covalent bonding between Al13 moiety and I in Al13I cluster isomers is Al13IBridge〉Al13IHollow〉Al13I Ontop. Further analysis of electric structures of Al13 and Al13I clusters indicates a higher stability of Al13I cluster than Al13 cluster can be attributed to the s-p hybridization of 3s and 3p electrons of Al in Al13 moiety induced by 1 doped, which leads to fewer electrons N（EF） at EF in Al13I and a larger energy gap △EH-L between HOMO and LUMO levels in Al13I cluster. The distinguish of structural stability of Al13I cluster isomers mainly originates from their different magnitudes .in decrease of N（EF） and increase of △EH-L relative to Al13 cluster. The fewest N（EF） and the largest △EH-L are responsible for the high stability of Al13I Bridge cluster.
文摘This paper gives a mathematical approach to calculate the fractionation factor of isotopes in a general cluster (also known as?super-molecule), which composes of necessary chemical effect within three bonds outside the interested atom(s). The cluster might have imaginary frequencies after being optimized in quantum softwares. The approach includes the contribution of the difference, which is resulted from the substitution of heavy and light isotopes in the cluster, of vibrations of imaginary frequencies to give precise prediction of isotope fractionation factor. We call the new mathematical approximation “reduced partition function ratio in the frequency complex plane (RPFRC)”. If there is no imaginary frequency for a cluster, RPFRC?is simplified to be Urey (1947) or Bigeleisen and Mayer (1947) formula. Final results of this new algorithm are in good agreement with those in earlier studies.
