An Online Fault Detection Model and Strategies Based on SVM-Grid in Clouds

Online fault detection is one of the key technologies to improve the performance of cloud systems. The current data of cloud systems is to be monitored, collected and used to reflect their state. Its use can potentially help cloud managers take some timely measures before fault occurrence in clouds. Because of the complex structure and dynamic change characteristics of the clouds, existing fault detection methods suffer from the problems of low efficiency and low accuracy. In order to solve them, this work proposes an online detection model based on asystematic parameter-search method called SVM-Grid, whose construction is based on a support vector machine(SVM). SVM-Grid is used to optimize parameters in SVM. Proper attributes of a cloud system's running data are selected by using Pearson correlation and principal component analysis for the model. Strategies of predicting cloud faults and updating fault sample databases are proposed to optimize the model and improve its performance.In comparison with some representative existing methods, the proposed model can achieve more efficient and accurate fault detection for cloud systems.

Quadratic Stabilization of Switched Uncertain Linear Systems: A Convex Combination Approach

We consider quadratic stabilization for a class of switched systems which are composed of a finite set of continuoustime linear subsystems with norm bounded uncertainties. Under the assumption that there is no single quadratically stable subsystem, if a convex combination of subsystems is quadratically stable, then we propose a state-dependent switching law, based on the convex combination of subsystems, such that the entire switched linear system is quadratically stable. When the state information is not available, we extend the discussion to designing an outputdependent switching law by constructing a robust Luenberger observer for each subsystem.

An Extended Convex Combination Approach for Quadratic L_(2)Performance Analysis of Switched Uncertain Linear Systems

Dear Editor,This letter is concerned with quadratic L_(2) performance(quadratic stability and L_(2) gain)for switched uncertain linear systems(SULS)with norm-bounded uncertainties.Assuming that no single uncertain subsystem achieves quadratic L_(2) performanceγbut a convex combination of the subsystems can make it,we propose a state-dependent switching law such that the SULS achieves the desired quadratic L_(2) performance.The discussion is extended to the SULS with state feedback control,and a sufficient condition is proposed to design the state feedback gains and the switching law simultaneously.

DVCast:denoising and variable dct for analog visual communications

Recently,analog visual transmission has attracted considerable attention owing to its graceful performance degradation for various wireless channels.In this study,we propose a novel analog visual communications system,named DVCast,in which an image denoising algorithm is used to fully utilize spatial correlation;moreover,the variable block size Discrete Cosine Transform(DCT)is used to preserve more correlation information in an image.Obviously,there is a tradeoff between system performance and computing complexity.Therefore,to improve the real-time performance of the proposed system,implementation of Block Matching with 3D filtering(BM3D)and DCT by Graphics Processing Units(GPUs)is introduced.According to DCT block size,i.e.,88,1616,and 3232,the schemes DVCast8,DVCast16,and DVCast32,respectively,are designed and implemented.Simulations show that DVCast with larger block size achieves better gain and visual quality than reference schemes.Moreover,it requires less computing time.DVCast32 outperforms conventional digital schemes by approximately 3.51 dB and achieves a 1.12 dB gain over state-of-the-art reference schemes.Furthermore,the analysis shows that DVCast can reduce overhead by at least 75%.