Interpretation of quasi-elastic light scattering data for flexible chains: model dependence

The autocorrelation functions and corresponding relaxation times obtained from the forward depolarized quasi-elastic light scattering experiment are exhibited for two quite similar models of flexible polymer chains in solution. A very small change in the chain dynamics is found to be sufficient to change the relaxation time from a relatively short time independent of chain length, with an autocorrelation function suggestive of an unweighted sum of contributions from all the relaxation times in the spectrum of chain motion, to a long time with an autocorrelation function identical with that for the end-to-end vector, strongly dependent upon chain length and dominated by the longest relaxation time in the spectrum. These results raise the question whether widely-used models in which information about short-range chain structure and motion is deliberately omitted can be expected to be appropriate for the interpretation of depolarized scattering experiments.     

End-to-end scene text recognition using tree-structured models

Detecting and recognizing text in natural images are quite challenging and have received much attention from the computer vision community in recent years. In this paper, we propose a robust end-to-end scene text recognition method, which utilizes tree-structured character models and normalized pictorial structured word models. For each category of characters, we build a part-based tree-structured model (TSM) so as to make use of the character-specific structure information as well as the local appearance information. The TSM could detect each part of the character and recognize the unique structure as well, seamlessly combining character detection and recognition together. As the TSMs could accurately detect characters from complex background, for text localization, we apply TSMs for all the characters on the coarse text detection regions to eliminate the false positives and search the possible missing characters as well. While for word recognition, we propose a normalized pictorial structure (PS) framework to deal with the bias caused by words of different lengths. Experimental results on a range of challenging public datasets (ICDAR 2003, ICDAR 2011, SVT) demonstrate that the proposed method outperforms state-of-the-art methods both for text localization and word recognition.     

基于随机网络演算的网络服务质量分析

为了提高网络的服务质量,提出一种基于随机网络演算的网络服务质量分析方法。首先推导出有效的端到端积压和时延边界,使到达流通过的节点数量呈线性增长;然后引入有效带宽和有效容量以延长到达流和服务进程的随机信息保留时间,可以更有效地计算端到端随机性能值;最后采用数据进行仿真实验,测试该方法的性能。结果表明,相对与其他网络服务质量分析方法,随机网络演算方法提高了网络的服务质量。     

Delay composition in preemptive and non-preemptive real-time pipelines

Uniprocessor schedulability theory made great strides, in part, due to the simplicity of composing the delay of a job from the execution times of higher-priority jobs that preempt it. In this paper, we bound the end-to-end delay of a job in a multistage pipeline as a function of job execution times on different stages under preemptive as well as non-preemptive scheduling. We show that the end-to-end delay is bounded by that of a single virtual “bottleneck” stage plus a small additive component. This contribution effectively transforms the pipeline into a single stage system. The wealth of schedulability analysis techniques derived for uniprocessors can then be applied to decide the schedulability of the pipeline. The transformation does not require imposing artificial per-stage deadlines, but rather models the pipeline as a whole and uses the end-to-end deadlines directly in the single-stage analysis. It also does not make assumptions on job arrival patterns or periodicity and thus can be applied to periodic and aperiodic tasks alike. We show through simulations that this approach outperforms previous pipeline schedulability tests except for very short pipelines or when deadlines are sufficiently large. The reason lies in the way we account for execution overlap among stages. We discuss how previous approaches account for overlap and point out interesting differences that lead to different performance advantages in different cases. Further, we also show that in certain cases non-preemptive scheduling can result in higher system utilization than preemptive scheduling in pipelined systems. We hope that the pipeline delay composition rule, derived in this paper, may be a step towards a general schedulability analysis foundation for large distributed systems.

服务组合中面向端到端用户QoS需求的QoS聚合机制研究

服务组合基于多种基本的组合结构,组合多个已有的服务来满足用户的功能性和非功能性(即QoS)需求。通常,用户的需求直接是端到端的需求,而服务描述本身具有自身的QoS描述。由于所处的层次不同,端到端的QoS需求描述和单个服务的QoS描述存在一定的语义鸿沟。基于层次化本体模型建立QoS本体模型,建立了用户QoS和服务QoS之间的映射关系。并针对基本的服务组合结构,研究了异构QoS本体环境下服务的QoS聚合机制。基于基本组合结构的QoS聚合,提出了完整的服务组合中的QoS聚合算法和QoS转换算法,以满足端到端的QoS需求。     

A novel heuristic algorithm for QoS-aware end-to-end service composition

Many works have been carried out to find the efficient algorithms for QoS-aware service composition in recent years. Nevertheless, on one hand, some of these works only consider the local QoS attributes in Web services composition; on the other hand, some ideas derived from QoS selection algorithms for network routing are directly applied in service composition without any adaption. A service composition model with end-to-end QoS constraints has been presented in this paper. An improved heuristics HCE based on the observation of characteristic of end-to-end service composition is proposed as a novel solution. Simulation results reveal the better performance of proposed heuristic compared to the other two heuristics, HMCOP and generic CE algorithm.     

高速以太网时延仿真分析

随着以太网技术的不断发展,以太网已成为未来通信领域的核心技术之一。而影响用户业务体验服务质量(QoS)的参数通常包括时延、抖动、丢包率等。对于实时的语音和视频业务来说,业务数据的端到端时延则最为关键。主要在熟悉以太网标准的基础上,总结端到端时延的主要构成因素,对各个时延所占比重进行理论分析。最后对10G/100G以太网进行仿真模型设计,验证了理论分析的正确性。     

领域需求的快速需求分析方法和辅助系统

介绍一种快速端到端的领域需求分析方法。结合辅助分析系统,快速实现需求分析,缩短开发周期,满足不断加剧的市场化竞争需要。     

UDP数据流对TCP流影响的分析和模拟

通过计算机模拟，说明了无拥塞控制的UDP数据流同TCP流共享带宽时的不公平性，并通过分析TCP的端到端流量控制机制指出了产生不公平的原因。     

Visualization workflows for level-12 HUC scales: Towards an expert system for watershed analysis in a distributed computing environment

Visualization workflows are important services for expert users to analyze watersheds when using our HydroTerre end-to-end workflows. Analysis is an interactive and iterative process and we demonstrate that the expert user can focus on model results, not data preparation, by using a web application to rapidly create, tune, and calibrate hydrological models anywhere in the continental USA (CONUS). The HydroTerre system captures user interaction for provenance and reproducibility to share modeling strategies with modelers. Our end-to-end workflow consists of four workflows. The first is data workflows using Essential Terrestrial Variables (ETV) data sets that we demonstrated to construct watershed models anywhere in the CONUS (Leonard and Duffy, 2013). The second is data-model workflows that transform the data workflow results to model inputs. The model inputs are consumed in the third workflow, model workflows (Leonard and Duffy, 2014a) that handle distribution of data and model within High Performance Computing (HPC) environments. This article focuses on our fourth workflow, visualization workflows, which consume the first three workflows to form an end-to-end system to create and share hydrological model results efficiently for analysis and peer review. We show how visualization workflows are incorporated into the HydroTerre infrastructure design and demonstrate the efficiency and robustness for an expert modeler to produce, analyze, and share new hydrological models using CONUS national datasets.