Visual attention guided bit allocation in video compression

A visual attention-based bit allocation strategy for video compression is proposed. Saliency-based attention prediction is used to detect interesting regions in video. From the top salient locations from the computed saliency map, a guidance map is generated to guide the bit allocation strategy through a new constrained global optimization approach, which can be solved in a closed form and independently of video frame content. Fifty video sequences (300 frames each) and eye-tracking data from 14 subjects were collected to evaluate both the accuracy of the attention prediction model and the subjective quality of the encoded video. Results show that the area under the curve of the guidance map is 0.773 ± 0.002, significantly above chance (0.500). Using a new eye-tracking-weighted PSNR (EWPSNR) measure of subjective quality, more than 90% of the encoded video clips with the proposed method achieve better subjective quality compared to standard encoding with matched bit rate. The improvement in EWPSNR is up to over 2 dB and on average 0.79 dB.     

移动云计算中基于协作式博弈模型的资源分配方案

提出一种基于协作式博弈的资源分配方案。首先, 在服务提供商创建长期可用预留资源公用库完毕后, 通过一种访问控制机制为用户提供移动应用服务, 提出一种优化算法实现访问控制的最优决策; 其次, 提出一种协作式博弈模型进行利益分配, 在服务提供商建立合作后, 通过使用资源公用库而获得的运营收入, 在服务提供商之间进行分配博弈。仿真实验结果表明, 该方法是有效的, 能够帮助服务提供商就容量提升制定最优策略, 以实现利益最大化。     

An efficient dynamic reliability-dependent bit allocation for biometric discretization

A biometric discretization scheme converts biometric features into a binary string via segmenting every one-dimensional feature space into multiple labelled intervals, assigning each interval-captured feature element with a short binary string and concatenating the binary output of all feature elements into a bit string. This paper proposes a bit allocation algorithm for biometric discretization to allocate bits dynamically to every feature element based on a Binary Reflected Gray code. Unlike existing bit allocation schemes, our scheme bases upon a combination of bit statistics (reliability measure) and signal to noise ratio (discriminability measure) in performing feature selection and bit allocation procedures. Several empirical comparative studies are conducted extensively on two popular face datasets to justify the efficiency and feasibility of our proposed approach.     

Regional bit allocation with visual attention and distortion sensitivity

This paper proposes a regional rate allocation method for enhancing the perceived quality in image compression. Bit allocation to image regions should be performed by considering the viewer’s attention and distortion sensitivity maps in order to address subjective quality concerns. The paper first proposes an exponential model for the relation between the viewer’s fixation duration and perceived information. The human visual system is more sensitive to the distortion around edges than the distortion in complex textured regions. Therefore, a novel distortion sensitivity method is also proposed that distinguishes true edges from complex textures without using edge detectors or gradient magnitude thresholds. The estimates for the visual attention level and the distortion sensitivity level are jointly used to modify the distortion contribution of each codeblock for determining its quantization parameter. The experiments validate the improved perceptual quality of decoded images due to the integrated use of the visual distortion sensitivity and the visual attention level in bit allocation. Moreover, the proposed bit allocation method is experimentally shown to yield a substantially higher subjective evaluation score than the other well-known bit allocation methods based on post-compression rate-distortion optimization, saliency maps, foveation of fixations and foveated just-noticeable-difference maps.

     

Cybersickness during VR gaming undermines game enjoyment: A mediation model

Recent advances in virtual reality (VR) technology have ushered in a new era of VR gaming. While VR gaming experience represents a burgeoning area of research within human-computer interaction circles, the role of cybersickness, physiological repercussions of VR exposure to users characterized by a multitude of symptoms, such as nausea, lightheadedness, and dizziness, in the effect of VR gaming on game enjoyment remains understudied. In two experiments, the current study proposed and tested a causal mediation model in which the effect of VR gaming on game enjoyment was mediated by the level of cybersickness experienced during the gameplay. Results from both experiments supported the proposed model and showed that increased cybersickness levels during VR gaming led to decreases in game enjoyment, indicating that cybersickness experienced during VR gaming undermines the enjoyment of the gaming experience. Results also revealed that compared to traditional desktop gaming, VR gaming invoked greater levels of cybersickness, but VR gaming did not lead to greater levels of game enjoyment. When the effect of cybersickness on game enjoyment was statistically removed, however, VR gaming was found to be more enjoyable. The current experiments provide preliminary evidence that cybersickness may hinder the enjoyment of VR gaming experience.     

Region-based rate control and bit allocation for wireless video transmission

In this paper, we propose a joint source-channel region-based rate control algorithm for real-time video transmissions over wireless systems. During the video transmission, the channel throughput available to the video encoder in the wireless systems is inherently variable, due to the retransmission of the error packets using the automatic repeat request (ARQ) error control. The variable data rate of the wireless system is characterized by the packet-level Gilbert two-state Markov Model, the parameters of which are extracted from the statistical properties of the channel information obtained from the wireless channel simulator. The proposed algorithm adopts a fast but effective block-based segmentation method to extract the regions of interest. Unlike traditional bit allocation methods used in the region/content-based rate control, the algorithm exploits the most effective criteria "coding qualities" as quantitative factors to directly control bit allocation among different regions so as to achieve better visual quality in the regions of interest. The computational complexity of the algorithm is low making it suitable for real-time applications. Compared with the MPEG-4 rate control algorithm, our algorithm can effectively enhance the perceptual quality for the regions of interest and significantly reduce the number of frame skipping; thereby, improve the smoothness of the video.     

A cloud supported model for efficient community health awareness

The needs for efficient and scalable community health awareness model become a crucial issue in today’s health care applications. Many health care service providers need to provide their services for long terms, in real time and interactively. Many of these applications are based on the emerging Wireless Body Area networks (WBANs) technology. WBANs have developed as an effective solution for a wide range of healthcare, military, sports, general health and social applications. On the other hand, handling data in a large scale (currently known as Big Data) requires an efficient collection and processing model with scalable computing and storage capacity. Therefore, a new computing paradigm is needed such as Cloud Computing and Internet of Things (IoT). In this paper we present a novel cloud supported model for efficient community health awareness in the presence of a large scale WBANs data generation. The objective is to process this big data in order to detect the abnormal data using MapReduce infrastructure and user defined functions with minimum processing delay. The goal is to have a large monitored data of WBANs to be available to the end user or to the decision maker in reliable manner. While reducing data packet processing energy, the proposed work is minimizing the data processing delay by choosing cloudlet or local cloud model and MapReduce infrastructure. So, the overall delay is minimized, thus leading to detect the abnormal data in the cloud in real time mode. In this paper we present a multi-layer computing model composed of Local Cloud (LC) layer and Enterprise Cloud (EP) layer that aim to process the collected data from Monitored Subjects (MSs) in a large scale to generate useful facts, observations or to find abnormal phenomena within the monitored data. Performance results show that integrating the MapReduce capabilities with cloud computing model will reduce the processing delay. The proposed MapReduce infrastructure has also been applied in lower layer, such as LC in order to reduce the amount of communications and processing delay. Performance results show that applying MapReduce infrastructure in lower tire will significantly decrease the overall processing delay.     

基于效益博弈的云计算资源动态可协调分配策略研究

在对用户的任务进行计算资源分配时,为了有效提高计算资源的利用效率,减少任务执行所需要的成本,提出了一种基于效益博弈的云计算资源动态可协调分配机制。该机制采用时间矩阵和费用矩阵作为任务效益的衡量指标,提出效益博弈模型,通过该模型的效益计算方程来得到最好的资源分配策略。为了使得计算资源能够合理地按需进行分配,提出了动态可协调分配机制,在合理地分配资源,满足所有任务正常执行时所需资源的同时,最大化任务的执行效益。实验仿真及对比结果表明,在任务完成时间、任务执行的平均成本、任务完成成功率上,本文算法都取得了较好的效果。     

A survey and taxonomy on energy efficient resource allocation techniques for cloud computing systems

In a cloud computing paradigm, energy efficient allocation of different virtualized ICT resources (servers, storage disks, and networks, and the like) is a complex problem due to the presence of heterogeneous application (e.g., content delivery networks, MapReduce, web applications, and the like) workloads having contentious allocation requirements in terms of ICT resource capacities (e.g., network bandwidth, processing speed, response time, etc.). Several recent papers have tried to address the issue of improving energy efficiency in allocating cloud resources to applications with varying degree of success. However, to the best of our knowledge there is no published literature on this subject that clearly articulates the research problem and provides research taxonomy for succinct classification of existing techniques. Hence, the main aim of this paper is to identify open challenges associated with energy efficient resource allocation. In this regard, the study, first, outlines the problem and existing hardware and software-based techniques available for this purpose. Furthermore, available techniques already presented in the literature are summarized based on the energy-efficient research dimension taxonomy. The advantages and disadvantages of the existing techniques are comprehensively analyzed against the proposed research dimension taxonomy namely: resource adaption policy, objective function, allocation method, allocation operation, and interoperability.     

A gamma fractal noise source model for variable bit rate video servers

In this paper, we model the statistical behavior of real traces of MPEG-4 encoded variable bit rate video data in a digital video server. As performance measures we calculate bounds for the user disk service rate and buffer size. According to our simulations, the Gamma Fractal Noise model for the increment process, which is self-similar, seems to be very close to the actual data behavior.     

CloudyGame: Enabling cloud gaming on the edge with dynamic asset streaming and shared game instances

Multimedia Tools and Applications - Cloud gaming has emerged as a new computer game delivery paradigm that promises gaming anywhere, anytime, on any device, by running the computer game on a cloud...     

A recursive algorithm for quick and efficient bit reversing

An algorithm to generate the permutation by bit reversal of the sequence of integers (0, 1,…,2ⁿ ? 1) is presented. To generate a sequence of length k = 2ⁿ the algorithm requires only k ? 1 additions and k ? 2 multiplications by 2. With respect to previous methods, the reduction of the computing time is O(log₂k).     

H.264/SVC比特自适应分配的等级B帧码率控制算法

为减少码率控制中实际输出码率与目标码率之间的误差,改善视频序列编码尾部质量下降的缺陷,同时针对可伸缩视频编码中码率控制算法的不足,提出一种自适应比特分配的码率控制算法。算法基于对根据相邻图像帧之间的相关性以及对恒定质量的考虑,在图像组(GOP)之间平均分配目标比特,而在GOP内部则根据编码复杂度自适应分配目标比特,同时适当调整初始量化参数(QP),再根据目标比特分别计算P帧、B帧的QP。对不同的视频序列进行了实验测试,其结果验证了算法的准确性和有效性。     

面向云平台中心化集成调度的跨供应商订单分配模型

跨供应商订单分配可以充分发挥云平台优势,有效整合利用各供应商的剩余资源.鉴于此,提出一种云平台主导的集成调度模式,基于该模式和供应商的产能约束、运输约束、订单约束构建面向云平台中心化集成调度的跨供应商订单分配模型,给出基于改进遗传算法的模型求解方法,并通过算例演示所构建模型和算法的有效性.Matlab实验结果表明,订单能够在各供应商间得以科学分配,实现各供应商闲置资源有效利用和成本最优.     

A population game approach for dynamic resource allocation problems

We consider a water distribution system as an example of resource allocation, and investigate the use of a population game for its control. We use a game-theoretic approach based on two evolutionary dynamics, the Brown–von Neumann–Nash and the Smith dynamics. We show that the closed-loop feedback interconnection of the water distribution system and the game-theoretic-based controller has a Nash equilibrium as an asymptotically stable equilibrium point. The stability analysis is performed based on passivity concepts and the Lyapunov stability theorem. An additional control subsystem is considered for disturbance rejection. We verify the effectiveness of the method by simulations under different scenarios.     

Pilot attention allocation model based on fuzzy theory

Quantitative research into a pilot’s attention allocation mechanism is required in the optimization design of an aircraft human-machine interface and system evaluation. After making a comprehensive consideration of several factors, including the importance of information, information detective efficiency and human errors, a pilot attention allocation model was built on the basis of hybrid entropy. In order to make a verification of the pilot attention allocation model, a simulation model of a head-up display (HUD) used to present flight indicators was developed. After setting the membership degrees of the importance for different indicators according to their priorities, the experiments on the key-press response and eye-movement tracking were designed and carried out under the cruise and hold modes. As the experiment results are in good agreement with the theoretical model, the effectiveness of the pilot attention allocation model based on fuzzy theory is confirmed.     

Content-aware rate allocation for efficient video streaming via dynamic network utility maximization

Nowadays it is vital to design robust mechanisms to provide QoS for multimedia applications as an integral part of the network traffic. The main goal of this paper is to provide an efficient rate control scheme to support content-aware video transmission mechanism with buffer underflow avoidance at the receiver in congested networks. Towards this, we introduce a content-aware time-varying utility function, in which the quality impact of video content is incorporated into its mathematical expression. Moreover, we analytically model the buffer requirements of video sources in two ways: first as constraints of the optimization problem to guarantee a minimum rate demand for each source, and second as a penalty function embedded as part of the objective function attempting to achieve the highest possible rate for each source. Then, using the proposed analytical model, we formulate a dynamic network utility maximization problem, which aims to maximize the aggregate hybrid objective function of sources subject to capacity and buffer constraints. Finally, using primal–dual method, we solve DNUM problem and propose a distributed algorithm called CA-DNUM that optimally allocates the shared bandwidth to video streams. The experimental results demonstrate the efficacy and performance improvement of the proposed content-aware rate allocation algorithm for video sources in different scenarios.     

Memory allocation algorithm for cloud services

Memory allocation has a major influence on multiuser systems, cloud-based services, virtual machines, and other computer systems. Memory allocation is a process that assigns physical or virtual memory space to programs and services as efficiently and quickly as possible. Economical memory allocation management needs allocation strategies with minimum wastage. In this paper, we introduce a new memory allocation algorithm based on sequential fits and zoning for on-demand (online) cloud services. The memory is divided into multiple zones, where a subgroup of relative request sizes compete in reverse order. We use simulation to compare our new mechanism with existing memory allocation methods that have been deployed using Amazon Elastic Compute Cloud as a test bed. The proposed algorithm is more efficient, and the average saving for the normalized revenue loss is about 7% better than best-fit and 15% better than first-fit memory allocation. In addition, we show that proposed algorithm is robust and faster and has a fairness index that is superior to that of existing techniques.     

Visual sensitivity guided bit allocation for video coding

A video bit allocation technique adopting a visual distortion sensitivity model for better rate-visual distortion coding control is proposed in this paper. Instead of applying complicated semantic understanding, the proposed automatic distortion sensitivity analysis process analyzes both the motion and the texture structures in the video sequences in order to achieve better bit allocation for rate-constrained video coding. The proposed technique evaluates the perceptual distortion sensitivity on a macroblock basis, and allocates fewer bits to regions permitting large perceptual distortions for rate reduction. The proposed algorithm can be incorporated into existing video coding rate control schemes to achieve same visual quality at reduced bitrate. Experiments based on H.264 JM7.6 show that this technique achieves bit-rate saving of up to 40.61%. However, the conducted subjective viewing experiments show that there is no perceptual quality degradation. EDICS-1-CPRS, 3-QUAL.