Cloud service-based applications are subject to reliability critical problem,as the reliability of the application relies on both the failed states and the probabilities of the failures.Classically,reliability analysi...Cloud service-based applications are subject to reliability critical problem,as the reliability of the application relies on both the failed states and the probabilities of the failures.Classically,reliability analysis approaches are lack of estimating unknown failure rate and non-exponentially distributed failure times.We propose a new framework for analyzing the reliability.The method is mainly decomposed in four successive steps:a non-Makovian stochastic Petri net(NMSPN)model which describes the failure behavior of underlying applications,a software reliability growth model(SRGM)which estimates the failure data of each basic service,a reachability graph which discoveries all the failure sequences,and a computation procedure which computes the occurrences of non-exponential failures.We assess and validate our method by conducting experiment on an actual application.The results demonstrate that the met hod is competitive compared to the existing approaches for reliability analysis,while providing a better reliability.This result is helpful to the managers in optimizing the overall quality of the cloud service-based application.展开更多
Acoustic echo cancellation is often applied in communication and video call system to reduce unnecessary echoes generated between speakers and microphones.In these systems,the speech input signal of the adaptive filte...Acoustic echo cancellation is often applied in communication and video call system to reduce unnecessary echoes generated between speakers and microphones.In these systems,the speech input signal of the adaptive filter is often colored and unstable,which decays the convergence rate of the adaptive filter if the NLMS algorithm is used.In this paper,an improved nonparametric variable step-size subband(NPVSS-NSAF)algorithm is proposed to address the problem.The variable step-size is derived by minimizing the sum of the square Euclidean norm of the difference between the optimal weight vectors to be updated and the past estimated weight vectors.Then the parameters are eliminated by using the power of subband signal noise equal to the power of subband posteriori error.The performance of the proposed algorithm is simulated in the aspects of misalignment and return loss enhancement.Experiment results show a fast convergence rate and low misalignment of the proposed algorithm in system identification.展开更多
基金the Special Fund of Major Information Platform Construction and Maintenance of the Ministry of Agriculture and Rural Affairs of China(No.2130104)。
文摘Cloud service-based applications are subject to reliability critical problem,as the reliability of the application relies on both the failed states and the probabilities of the failures.Classically,reliability analysis approaches are lack of estimating unknown failure rate and non-exponentially distributed failure times.We propose a new framework for analyzing the reliability.The method is mainly decomposed in four successive steps:a non-Makovian stochastic Petri net(NMSPN)model which describes the failure behavior of underlying applications,a software reliability growth model(SRGM)which estimates the failure data of each basic service,a reachability graph which discoveries all the failure sequences,and a computation procedure which computes the occurrences of non-exponential failures.We assess and validate our method by conducting experiment on an actual application.The results demonstrate that the met hod is competitive compared to the existing approaches for reliability analysis,while providing a better reliability.This result is helpful to the managers in optimizing the overall quality of the cloud service-based application.
基金This work was supported by the National Key Research and Development Program of China(Grant No.2018YFF0213602).
文摘Acoustic echo cancellation is often applied in communication and video call system to reduce unnecessary echoes generated between speakers and microphones.In these systems,the speech input signal of the adaptive filter is often colored and unstable,which decays the convergence rate of the adaptive filter if the NLMS algorithm is used.In this paper,an improved nonparametric variable step-size subband(NPVSS-NSAF)algorithm is proposed to address the problem.The variable step-size is derived by minimizing the sum of the square Euclidean norm of the difference between the optimal weight vectors to be updated and the past estimated weight vectors.Then the parameters are eliminated by using the power of subband signal noise equal to the power of subband posteriori error.The performance of the proposed algorithm is simulated in the aspects of misalignment and return loss enhancement.Experiment results show a fast convergence rate and low misalignment of the proposed algorithm in system identification.
