Fault Aware Dynamic Resource Manager for Fault Recognition and Avoidance in Cloud

Fault tolerance(FT)schemes are intended to work on a minimized and static amount of physical resources.When a host failure occurs,the conventional FT frequently proceeds with the execution on the accessible working hosts.This methodology saves the execution state and applications to complete without disruption.However,the dynamicity of open cloud assets is not seen when taking scheduling choices.Existing optimization techniques are intended in dealing with resource scheduling.This method will be utilized for distributing the approaching tasks to the VMs.However,the dynamic scheduling for this procedure doesn’t accomplish the objective of adaptation of internal failure.The scheme prefers jobs in the activity list with the most elevated execution time on resources that can execute in a shorter timeframe,but it suffers with higher makespan;poor resource usage and unbalance load concerns.To overcome the above mentioned issue,Fault Aware Dynamic Resource Manager(FADRM)is proposed that enhances the mechanism to Multi-stage Resilience Manager at an application-level FT arrangement.Proposed FADRM method gives FT a Multi-stage Resilience Manager(MRM)in the client and application layers,and simultaneously decreases the over-head and degradations.It additionally provides safety to the application execution considering the clients,application and framework necessities.Based on experimental evaluations,Proposed Fault Aware Dynamic Resource Manager(FADRM)method 157.5 MakeSpan(MS)time,0.38 Fault Rate(FR),0.25 Failure Delay(FD)and improves 5.5 Performance Improvement Ratio(PIR)for 25,50,75 and 100 tasks and 475 MakeSpan(MS)time,0.40 Fault Rate(FR),1.30 Failure Delay(FD)and improves 6.75 improves Performance Improvement Ratio(PER)for 100,200,300 and 500 Tasks compare than existing methodologies.

New Technique for Estimating and Suppressing Narrowband Interference in DSSS Systems

A generalized approach for narrowband interference （NBI） suppression in direct sequence spread spectrum （DSSS） communication systems using adaptive infinite impulse response （IIR） filter is presented. The excision filter coefficients depend on both the jammer power and its instantaneous frequency. The dependency of the filter construction on the jammer power is significant as it allows optimal tradeoff between interference removal and signal distortion by maximizing the receiver signal to noise ratio improvement（SNRI）. Instead of traditional adaptive line enhancer （ALE） estimator, a preferable NBI estimator-Fourier interpolation estimator （FIE） is proposed. Closed-form expressions of the SNR improvement and theoretical bit error rate （BER） based on the assumption that the output of the correlator is Gaussian distributed are both derived. Performance results obtained by numerical simulation are also presented and compared with theoretical results.

Noise reduction and signal to noise ratio improvement in magneto-optical polarization rotation measurement

The measurement of an extremely small magneto-optical polarization rotation angle with high sensitivity is integral to many scientific and technological applications. In this Letter, we have presented a technique based on Faraday modulation combined with the optical differential method to measure an extremely small polari- zation rotation angle with high sensitivity. The theoretical and experimental results show that common mode noise is reduced appreciably and signal to noise ratio is enhanced. The effectiveness of this technique has been demonstrated by measuring the Verdet constant of terbium gallium garnet glass and measuring the small polari- zation rotation angle. A sensitivity of enhancement of one order of magnitude has been achieved using differ- ential detection based on Faraday modulation.

Improved Support Vector Machine Approach Based on Determining Thresholds Automatically

To improve the training speed of support vector machine （SVM）, a method called improved center distance ratio method （ICDRM） with determining thresholds automatically is presented here without reduce the identification rate. In this method border vectors are chosen from the given samples by comparing sample vectors with center distance ratio in advance. The number of training samples is reduced greatly and the training speed is improved. This method is used to the identification for license plate characters. Experimental resuhs show that the improved SVM method-ICDRM does well at identification rate and training speed.

Imaging process and signal-to-noise ratio improvement of enhanced self-heterodyne synthetic aperture imaging ladar

This Letter gives the general construction of an enhanced self-heterodyne synthetic aperture imaging ladar（SAIL） system, and proposes the principle of image processing. A point target is reconstructed in the enhanced self-heterodyne SAIL as well as in down-looking SAIL experiments, and the achieved imaging resolution of the enhanced self-heterodyne SAIL is analyzed. The signal-to-noise ratio（SNR） of the point target final image in the enhanced self-heterodyne SAIL is higher than that in the down-looking SAIL. The enhanced self-heterodyne SAIL can improve the SNR of the target image in far-distance imaging, with practicality.

Simple and effective method to improve the signal-to-noise ratio of compressive imaging

This Letter presents a simple and effective method to improve the signal-to-noise ratio（SNR） of compressing imaging. The main principles of the proposed method are the correlation of the image signals and the randomness of the noise. Multiple low SNR images are reconstructed firstly by the compressed sensing reconstruction algorithm, and then two-dimensional time delay integration technology is adopted to improve the SNR. Results show that the proposed method can improve the SNR performance efficiently and it is easy to apply the a lgorithm to the real project.