An energy-efficient cloud system with novel dynamic resource allocation methods

The Journal of Supercomputing - In the last decade, cloud computing has brought enormous changes to people’s lives. Cloud computing gives a client-driven computational model. In this case,...     

Digital audio watermarking using minimum-amplitude scaling on optimized DWT low-frequency coefficients

This work presents an audio watermarking scheme using minimum-amplitude scaling on the optimized lowest-frequency coefficients in the wavelet domain. Signal-to-noise ratio (SNR), bit-error-rate (BER) and Perceptual Evaluation of Audio Quality (PEAQ) are commonly utilized performance indexes in measuring the fidelity, robustness and quality of watermarking algorithms. However, there is a tradeoff relationship between audio quality and robustness. To overcome the drawback, this paper aims in proposing an optimization-based scaling scheme using optimal modification of low-frequency amplitude in the wavelet domain. A function connecting the multi-coefficients, composed of arbitrary scaling on the lowest DWT coefficients, and the group SNR of these coefficient is derived. Karush-Kuhn-Tucker (KKT) theorem and minimum length play two essential roles to obtain the optimal modification of low-frequency amplitude with optimal scaling factors. Furthermore, the almost invariant feature of these optimized scaling factors hold demonstrates resistance to amplitude modification manipulation. To practically evaluate the watermarked audio quality, an objective measurement using the PEAQ is also performed as well. Experimental results confirm that the embedded audio in the proposed method has high SNR, low BER, and good PEAQ, indicating strong robustness against various attacks, such as re-sampling, amplitude modification, and mp3 compression.

     

Adaptive audio watermarking via the optimization point of view on the wavelet-based entropy

This study aims to present an adaptive audio watermarking method using ideas of wavelet-based entropy (WBE). The method converts low-frequency coefficients of discrete wavelet transform (DWT) into the WBE domain, followed by the calculations of mean values of each audio as well as derivation of some essential properties of WBE. A characteristic curve relating the WBE and DWT coefficients is also presented. The foundation of the embedding process lies on the approximately invariant property demonstrated from the mean of each audio and the characteristic curve. Besides, the quality of the watermarked audio is optimized. In the detecting process, the watermark can be extracted using only values of the WBE. Finally, the performance of the proposed watermarking method is analyzed in terms of signal to noise ratio, mean opinion score and robustness. Experimental results confirm that the embedded data are robust to resist the common attacks like re-sampling, MP3 compression, low-pass filtering, and amplitude scaling.     

Emergency Evacuation Planning via the Point of View on the Relationship Between Crowd Density and Moving Speed

Wireless Personal Communications - Emergency evacuation is concerning to both industry and academics. This work applied the technology of a wireless sensor network to design and propose a nonlinear...     

Improvement of workload balancing using parallel loop self-scheduling on Intel Xeon Phi

In recent years, Intel promotes its new product Xeon Phi coprocessor, which is similar to the x86 architecture coprocessor. It has about 60 cores and can be regarded as a single computing node, with the computing power that cannot be ignored. This work aims to improve the workload balance by parallel loop self-scheduling scheme performed on Xeon Phi-based computer cluster. The proposed concept is implemented by hybrid MPI and OpenMP parallel programming in C language. Since parallel loop self-scheduling composes of static and dynamic allocation, weighting algorithm is adopted in the static part, while the well-known loop self-scheduling is adopted in dynamic part. The loop block is partitioned according to the weighting of MIC and HOST nodes. Accordingly, Xeon Phi with many-core is adopted to implement parallel loop self-scheduling. Finally, we test the performance in the experiments by four applicable problems: matrix multiplication, sparse matrix multiplication, Mandelbrot set and circuit meet. The experimental results indicate how to do the weight allocation and which scheduling method can achieve the best performance.