A systematic approach for end-to-end QoS qualitative diagnosis and quantitative guarantee is proposed to support quality of service （QoS） management on current Internet. An automatic unwatched discretization algorit...A systematic approach for end-to-end QoS qualitative diagnosis and quantitative guarantee is proposed to support quality of service （QoS） management on current Internet. An automatic unwatched discretization algorithm for discretizing continuous numeric-values is brought forth to reshape these QoS metrics and contexts into their discrete forms. For QoS qualitative diagnosis, causal relationships between a QoS metric and its contexts are exploited with K2 Bayesian network （BN） structure learning by treating QoS metrics and contexts as BN nodes. A QoS metric node is qualitatively diagnosed to be causally related to its parent context nodes. To guarantee QoS quantitatively, those causal relationships are next modeled quantitatively by BN parameter learning. Then, BN inference can be carried out on the BN. Finally, the QoS metric is guaranteed to a specific value with certain probability by tuning its causal contexts to suitable values suggested by the BN inference. Our approach is validated to be sound and effective by simulations on a peer-to-peer （P2P） network.展开更多
In recent years,context aware technology has been widely used in many fields,such as internet of vehicles(IoV).Consistent context information plays a vital role in adapting a system to rapidly changing situations.Howe...In recent years,context aware technology has been widely used in many fields,such as internet of vehicles(IoV).Consistent context information plays a vital role in adapting a system to rapidly changing situations.However,sensor's precision variance,equipment heterogeneity,network delay and the difference of statistical algorithms can lead to inconsistency context and inappropriate services.In this paper,we present an effective algorithm of context inconsistent elimination which is based on feedback and adjusted basic reliability distribution.Through feedback,each sensor's perception precision can be obtained,and with the adjusted basic reliability distribution scheme,we can make full use of all context information by adjusting the influence of every context on whole judgment based on sensor's perception precision and threshold of sensor's perception precision,and then eliminate context inconsistency.In order to evaluate the performance of the proposed context inconsistency elimination algorithm,context aware rate is defined.The simulation results show that the proposed context inconsistency elimination algorithm can obtain the best context aware rate in most cases for the varied error rates of sensors.展开更多
We introduce some ways to compute the lower and upper bounds of the Laplace eigenvalue problem.By using the special nonconforming finite elements,i.e.,enriched Crouzeix-Raviart element and extended Q1ro t,we get the l...We introduce some ways to compute the lower and upper bounds of the Laplace eigenvalue problem.By using the special nonconforming finite elements,i.e.,enriched Crouzeix-Raviart element and extended Q1ro t,we get the lower bound of the eigenvalue.Additionally,we use conforming finite elements to do the postprocessing to get the upper bound of the eigenvalue,which only needs to solve the corresponding source problems and a small eigenvalue problem if higher order postprocessing method is implemented.Thus,we can obtain the lower and upper bounds of the eigenvalues simultaneously by solving eigenvalue problem only once.Some numerical results are also presented to demonstrate our theoretical analysis.展开更多
基金Supported by the National High Technology Research and Development Program of China （No. 2007AA010302, 2009AA012404） the National Basic Research Program of China （No. 2007CB307103）+1 种基金 the National Natural Science Foundation of China （No. 60432010, 60802034） the Specialized Research Fund for the Doctoral Program of Higher Education （No. 20070013026）.
文摘A systematic approach for end-to-end QoS qualitative diagnosis and quantitative guarantee is proposed to support quality of service （QoS） management on current Internet. An automatic unwatched discretization algorithm for discretizing continuous numeric-values is brought forth to reshape these QoS metrics and contexts into their discrete forms. For QoS qualitative diagnosis, causal relationships between a QoS metric and its contexts are exploited with K2 Bayesian network （BN） structure learning by treating QoS metrics and contexts as BN nodes. A QoS metric node is qualitatively diagnosed to be causally related to its parent context nodes. To guarantee QoS quantitatively, those causal relationships are next modeled quantitatively by BN parameter learning. Then, BN inference can be carried out on the BN. Finally, the QoS metric is guaranteed to a specific value with certain probability by tuning its causal contexts to suitable values suggested by the BN inference. Our approach is validated to be sound and effective by simulations on a peer-to-peer （P2P） network.
基金supported by Scientific Research Foundation for the Excellent Young and Middle-aged Scientists of Shandong Province(No.BS2012DX024)Independent Innovation Foundation of Shandong University(No.2012ZD035)Technical Innovative Project of Shandong Province(No.201230201031,No.201320201024)
文摘In recent years,context aware technology has been widely used in many fields,such as internet of vehicles(IoV).Consistent context information plays a vital role in adapting a system to rapidly changing situations.However,sensor's precision variance,equipment heterogeneity,network delay and the difference of statistical algorithms can lead to inconsistency context and inappropriate services.In this paper,we present an effective algorithm of context inconsistent elimination which is based on feedback and adjusted basic reliability distribution.Through feedback,each sensor's perception precision can be obtained,and with the adjusted basic reliability distribution scheme,we can make full use of all context information by adjusting the influence of every context on whole judgment based on sensor's perception precision and threshold of sensor's perception precision,and then eliminate context inconsistency.In order to evaluate the performance of the proposed context inconsistency elimination algorithm,context aware rate is defined.The simulation results show that the proposed context inconsistency elimination algorithm can obtain the best context aware rate in most cases for the varied error rates of sensors.
基金supported by National Science Foundations of China (Grant Nos. 11001259,11031006)Croucher Foundation of Hong Kong Baptist University
文摘We introduce some ways to compute the lower and upper bounds of the Laplace eigenvalue problem.By using the special nonconforming finite elements,i.e.,enriched Crouzeix-Raviart element and extended Q1ro t,we get the lower bound of the eigenvalue.Additionally,we use conforming finite elements to do the postprocessing to get the upper bound of the eigenvalue,which only needs to solve the corresponding source problems and a small eigenvalue problem if higher order postprocessing method is implemented.Thus,we can obtain the lower and upper bounds of the eigenvalues simultaneously by solving eigenvalue problem only once.Some numerical results are also presented to demonstrate our theoretical analysis.
