Service-oriented smart home applications: composition, code generation, deployment, and execution

A smart home usually has a variety of devices or home appliance, instead of designing software for a specific home, this paper proposes a service-oriented framework with a set of ontology systems to support service and device publishing, discovery of devices and their services, composition of control software using existing control services that wrap devices, deployment, and execution of the composed service in an computing environment, monitoring the execution, and recovery from device failure. The ontology systems specify semantic information about devices, services, and workflows used in various smart home, and users can compose and recompose services for their specific needs. New devices, workflows, and services can be added into ontology. Most of the steps in this process can be automated including code generation. For example, service composition will be carried out in three steps: abstract workflow design, function construction, and device discovery, and different codes can be generated for different computing platforms such as Java and Open Services Gateway initiative environments. In this way, a variety of smart home can be constructed rapidly using the framework by discovery and composition using existing services and workflows. This paper illustrates this framework using a media control example to illustrate the ontology, discovery, composition, deployment, execution, monitoring, and recovery.     

Reward only is not enough: Evaluating and improving the fairness policy of the P2P file sharing network eMule/eDonkey

Limiting the threat of free-riding behavior is an important design issue for peer-to-peer (P2P) file sharing networks. However, the fairness policy that rewards contributors with credit in one of the most popular P2P file sharing networks, eMule/eDonkey, hasn’t been thoroughly studied. In this paper, motivated by our experiments with the eMule/eDonkey network, we firstly theoretically analyze the content exchange process with credit in eMule/eDonkey and then verify the mathematical model by an agent-based simulation. Both the numerical and simulation-based results confirm our discovery in the experiments that eMule/eDonkey’s local credit strategy can not provide enough fairness as it doesn’t explicitly punish free-riders. To overcome this drawback, we propose a new free-riding control scheme, which can simply maintain the current credit local structure and take advantage of the credit policy. Extensive numerical evaluation and simulation indicate that this scheme significantly improves system fairness.     

A new parallel particle filter face tracking method based on heterogeneous system

This paper proposed a multi-cue-based face-tracking algorithm with the supporting framework using parallel multi-core and one Graphic Processing Unit (GPU). Due to illumination and partial-occlusion problems, face tracking usually cannot stably work based on a single cue. Focusing on the above-mentioned problems, we first combined three different visual cues??color histogram, edge orientation histogram, and wavelet feature??under the framework of particle filters to considerably improve tracking performance. Furthermore, an online updating strategy made the algorithm adaptive to illumination changes and slight face rotations. Subsequently, attempting two parallel approaches resulted in real-time responses. However, the computational efficiency decreased considerably with the increase of particles and visual cues. In order to handle the large amount of computation costs resulting from the introduced multi-cue strategy, we explored two parallel computing techniques to speed up the tracking process, especially the most computation-intensive observational steps. One is a multi-core-based parallel algorithm with a MapReduce thread model, and the other is a GPU-based speedup approach. The GPU-based technique uses features-matching and particle weight computations, which have been put into the GPU kernel. The results demonstrate that the proposed face-tracking algorithm can work robustly with cluttered backgrounds and differing illuminations; the multi-core parallel scheme can increase the speed by 2?C6 times compared with that of the corresponding sequential algorithms. Furthermore, a GPU parallel scheme and co-processing scheme can achieve a greater increase in speed (8×?C12×) compared with the corresponding sequential algorithms.     

A group priority earliest deadline first scheduling algorithm

In most priority scheduling algorithms, the number of priority levels is assumed to be unlimited. However, if a task set requires more priority levels than the system can support, several jobs must in practice be assigned the same priority level. To solve this problem, a novel group priority earliest deadline first (GPEDF) scheduling algorithm is presented. In this algorithm, a schedulability test is given to form a job group, in which the jobs can arbitrarily change their order without reducing the schedulability. We consider jobs in the group having the same priority level and use shortest job first (SJF) to schedule the jobs in the group to improve the performance of the system. Compared with earliest deadline first (EDF), best effort (BE), and group-EDF (gEDF), simulation results show that the new algorithm exhibits the least switching, the shortest average response time, and the fewest required priority levels. It also has a higher success ratio than both EDF and gEDF.     

复杂场景实时目标检测方法

针对含有非平稳背景的复杂场景,提出一种基于空间混合高斯模型的实时目标检测方法.该方法以混合高斯模型作为颜色分布的统计框架,并在空间邻域中利用背景与前景隶属度之间的竞争确定像素的归属,提高了检测准确率;同时通过基于偏差均值的匹配判断和低权重模型的移除提升了混合高斯统计框架的性能,以实时地对运动目标进行准确的检测.实验结果表明,文中方法对非平稳背景有很好的适应能力,在检测准确率和运行效率上均优于其他检测方法.     

V型立体纸雕的几何理论与算法的研究

立体书是一种独特的纸张艺术形式,有着精细的几何结构.针对一类特殊的V型立体纸雕进行了系统性的研究,给出了V型立体纸雕可实现性的充分条件,使其可以只借助2张支撑面的力量进行打开和关闭,同时在这个过程中所有的面片都保持刚性并且相互不产生自交.基于这些充分条件,文中分别实现了一个计算机辅助交互V型纸雕设计工具,以及一个基于体方法的自动生成算法.     

基于AROP程序包的类Landsat遥感影像配准与正射纠正试验和精度分析

遥感影像的精确配准和正射纠正是进行图像融合、变化检测、图像镶嵌、定量遥感建模、多时相和多传感器影像协同应用的基础和前提。以美国国家航空和航天管理局下设LEDAPS(Landsat Ecosystem Disturbance Adaptive Processing System)课题组开发的配准与正射纠正程序包AROP(Automated Registration and Orthorectification Package)为例,详细阐述了其配准的原理与程序设计流程,并对其配准的精度进行了分析和评价。试验表明:AROP程序包算法能够找出足够的控制点,且控制点分布较为均匀,配准误差小于0.5个像元。误差特征表现为:扫描误差明显大于航向误差,误差的结果与影像漂移、DEM、坡度存在一定的相关性,高程和坡度是影响配准精度的主要因素之一。该程序包目前能够用于对我国CBERS影像的正射校正以及波段不匹配处理,但是对HJ卫星CCD影像数据配准还有待于进一步研究。     

基于区间树硬件加速索引的Marching Cubes算法

为了充分利用GPU的海量线程并行架构,提高等值面可视化效率,提出一种基于区间树硬件加速索引的Marching Cubes算法.该算法在预计算阶段利用GPU构造多区域的区间树作为体数据体素的值域索引;在实时运行阶段根据用户给定的阈值,通过该索引并行地搜索活跃体素,并生成活跃体素的多级索引,然后分配线程处理活跃体素,抽取并绘制等值面.将文中算法应用到不同体数据上的实验结果表明,其能够显著地提高现有Marching Cubes算法的效率;与现有的GPU基准算法相比,最高能达到4～10倍的加速比.     

基于模型修正技术的模拟集成电路几何规划优化方法

为了兼顾模拟集成电路设计优化的求解精度和计算效率,提出一种基于正项式模型修正技术的几何规划优化方法.首先将模拟集成电路的设计目标与约束简化为正项式模型,然后在采用几何规划方法迭代优化的过程中利用晶体管级SPICE仿真不断修正这一正项式模型.实例表明,与传统基于公式的优化方法和基于仿真的优化方法相比,该方法能够在尽量保证计算效率和全局最优解的前提下使优化精度满足晶体管级SPICE仿真的要求.