206840947
AppManager: a powerful service-based application management system for clusters
Cluster application management plays an important role in cluster systems. With more and more applications being settled on clusters, application management faces more and more challenging requirements. This paper introduces a service-based cluster application management system called AppManager. Different from traditional job management systems, AppManager has a service-based architecture. The components of a job management system are modularized and encapsulated into services. All these services are accessible within a cluster or outsides over Internet. Besides the basic functions of a traditional application management system, such as resource management, application schedule and control, AppManager implements many excellent features including supporting a wide variety of application types, platform flexibility, high system scalability, high availability assurance for application, scheduling algorithm extensibility and so on.
39810254
NCPN: A Simulation Tool for Coloured Petri Nets
17488833
Bandwidth adaptive quality smoothing for unequal error protected scalable video streaming
Summary form only given. We address the problem of inter-GOF bit allocation for FEC-MDC protected scalable video sequences. The objective is to minimize the variation in quality while streaming over packet-loss channels with time-varying bandwidth. We present an online heuristic algorithm to adaptively allocate bits for every GOF. Before transmitting a GOF, we first estimate the current available network bandwidth, and calculate the spare channel bit rate available to be used for current GOF. Then we propose a novel AIMD (additive increase/multiplicative decrease) quality control mechanism to regulate the changing behavior of target quality: (a) if the spare channel bit rate is greater than a certain value, then we increase the target quality gracefully in a linear mode; (b) else if it is less than another certain value, then we decrease the target quality aggressively. Finally, once the target quality is determined, we allocate bits for current GOF to meet the target quality requirement by iteratively increasing or decreasing the packet length used by FEC-MDC packetization. Since this procedure is time costly, we propose a fast approximate-approaching based dual-stage iteration technique to accelerate it. Experimental results show that our techniques can achieve near constant or graceful increasing quality in a segment by segment scheme, and the improved algorithm is very efficient and can be used in real-time online computation. Besides, we also analyze the impacts of some algorithm parameters to the quality smoothing results.
17033728
A Visual Perceiving and Eyeball-Motion Controlling Neural Network for Object Searching and Locating
This paper proposes a visual cognitive neural network for automatic object searching and locating. The model consists of two sub-networks. One is a visual perceiving network, which simulates human eyes to input image signals and recognize an object's direction and distance in terms of a high-level perceiving neuron's maximum response. The other one is an eyeball-motion controlling network, which simulates that human brain's high-level perceiving neurons transfer their responses to eyeball-motion controlling muscle cells to change eye's gaze to the position of the object that the perceiving system is attentive to or interested in. The system is applied to human face features searching and experiments show a promising result.
15856113
Rate control for advance video coding (AVC) standard
Rate control plays a very important role in constant bit rate (CBR) coding. AVC standard is jointly developed by ISO and ITU-T, which contains several inter and intra prediction modes. Rate distortion optimization (RDO) based on prerequisite quantization parameters determines the optimal prediction of each macroblock. This makes the current AVC software difficult to adopt the existing rate control techniques. This paper proposes an efficient rate control algorithm at macroblock level for AVC standard by considering both rate control and optimal prediction selection. Firstly, a quantization parameter estimated from neighboring macroblock is used in selecting an initial prediction and calculating the activity. Secondly, the estimated quantization parameter is refined according to the activity and virtual buffer occupancy. At last, the prediction mode is determined with the refined quantization parameter. Experimental results show that the proposed rate control algorithm can accurately achieve the target bit rate. Furthermore, the coding efficiency is similar to or even better than that of variable bit rate (VBR) coding.
12689128
Region-based visual attention analysis with its application in image browsing on small displays
Visual attention has been a hot research point for many years and many new applications are emerging especially for wireless multimedia services. In this paper a novel region-based visual attention is proposed to detect the Regions of Interest (ROI) of images. In the proposed method, density based image segmentation is first performed by regarding region as the perceptive unit, which makes the model robust to the scale of ROIs and contains more perceptive information. To generate region saliency map to detect ROI, global effect and contextual difference are covered in the form of distance factor and adjacency factor respectively. Since different ROIs may have different importance for different purposes, a ROI ranking algorithm is designed for browsing large images on small displays. Experimental results and evaluation reveal that our method works effectively to detect ROIs from images and the users are satisfied with the browsing sequence on small displays.
20145471
Spatial Video Watermarking Based on Stability of DC Coefficients
Watermarking technology plays an important role in digital rights management. Many high performance watermark algorithms have been developed. However, most of them focused on image media. This paper presents a novel blind video watermarking algorithm based on the stability of the direct current (DC) coefficient values in blocks. This algorithm first selects some frames by a key, and then embeds watermark into its luminance component of each selected frame. The luminance component to be watermarked first is divided into sub-blocks with size 8 by 8, and then discrete cosine transform (DCT) is used to process each sub-block to get the DC coefficients. Rearranging these DC coefficients into sub-sequences with equal length, and each such sub-sequence is transformed by DCT and get the highest frequency coefficient. Finally, the watermark is embedded in the high frequency coefficient array. The correlation metric is used in the detection process. The experimental results indicate that the correlation curve peaks emerge at the watermarked I frames and P frames which suffered from MPEG-4 and H.264 compression. The proposed watermarking method has strong robustness against some attacks such as frame deleting, frame inserting, frame shifting, frame statistical average and collusion attack.