基于 OpenStack 的虚拟资源调度技术研究

传统的高能物理计算系统基于物理机集群,主要通过 Torque、Condor、LSF 等资源管理和作业调度系统将作业调度到物理机器上运行,缺少对虚拟化计算的接口支持。我们选取 OpenStack 作为底层虚拟化平台,设计并实现上层调度系统与 OpenStack 之间的桥梁,采用推拉结合的作业运行方式,构建虚拟计算集群。     

An Intents-based approach for dynamic service discovery

Service discovery has been a very active research field attracting many researchers around the world. Most of the previous research efforts on service discovery have been based on the ternary classification of participant roles in web services, including service providers, brokers, and consumers. This classification is insufficient because it fails to make a difference between application developers and end users who both belong to service consumers. As a result, application developers usually take the responsibility of seeking services while end users who ultimately use the application are ignored. In order to address this issue, this paper presents an Intents-based approach for dynamic service discovery. The proposed approach is motivated from two industrial protocols: Android Intents and web Intents. It improves the two protocols by a generic model from the aspects of architecture, intent messages and their resolving process, Intents services, and user agents. It classifies the implicit intents into authoritative and naïve intents and is compatible with the current web service triangular architecture. This paper also illustrates a way of creating Intents services from SOAP and REST web services and presents two cases to demonstrate some benefits of the proposed approach.     

基于光纤陀螺的水布垭水电站大坝面板挠度变形规律分析

水布垭水电站混凝土面板堆石坝采用光纤陀螺(FOG)监测面板挠度变形。通过对监测资料分析,全面揭示了水布垭面板堆石坝面板挠度变形特点和一般规律,即:面板挠度变形整体趋于收敛,坝高1/3附近和运行低水位高程附近面板反弹出现峰值。监测成果为大坝安全运行提供重要依据。     

全球河流入海沙量估算述评

全球河流入海沙量作为地球系统运行变化的重要而敏感的指标,在一定程度上会对全球社会、经济和环境问题产生重要影响,从而引起国内外研究者的高度关注。针对由于缺乏可靠、完整的河流输沙量数据,很难准确估算全球河流入海沙量的数值及其变化,且已有文献估算值差别很大,缺乏统一认识的问题,收集整理了20世纪50年代至今国内外27篇文献中全球河流入海沙量的估算值,并对近期相关典型研究成果进行述评。调查发现,早期估算的入海沙量数值差异很大,随着人们对这一问题的深入研究,近年来全球入海沙量估算值日趋合理,大多集中在120亿~200亿t/a。分析认为,人类活动影响前后的河流入海沙量宜分别按190亿t/a和130亿t/a考虑。     

Algorithm of gaussian sum filter based on high-order UKF for dynamic state estimation

In this work we consider the state estimation problem in nonlinear/non-Gaussian systems. A new version of Gaussian sum estimation algorithm is developed here based on high-order unscented Kalman filter (HUKF). A sigma point selection method, high-order unscented transformation (HUT) technique is proposed for the HUKF, which can approximate the Gaussian distributions more accurately. We present the systematic formulation of Gaussian filters and develop efficient and accurate numerical integration of the optimal filter. We then go on to extend the use of the HUKF to discrete-time, nonlinear systems with additive, possibly non-Gaussian noise. The resulting filtering algorithm, called the Gaussian sum high-order unscented Kalman filter (GS-HUKF) approximates the predicted and posterior densities as a finite number of weighted sums of Gaussian densities. It is corroborated in the theoretical analysis and the simulation that the proposed Gaussian sum HUKF has integrated advantages with respect to computational accuracy and time complexity for nonlinear non-Gaussian filtering problems.     

Design optimization of a runflat structure based on multi-objective genetic algorithm

Runflat structure plays an important role in determining the sustainable mileage after the tire is shot. Lightweight, stiffness and strength are highly relevant to the overall performance of the structure. A parameterized model was built based on the full study of the structure, and a new adaptive meshing method is proposed to ensure the quality of the model. The accuracy of the new model was verified by comparing to the traditional finite element model. The parameter study was carried out to investigate the response of the performance and mass. Multi-objective optimization model was established by applying optimal Latin square design method and response surface model approach. Non-dominated sorting genetic algorithm-II (NSGA-II) was applied to obtain the optimization design. The results indicate that the combination of parameterized model and multi-objective genetic algorithms successfully achieve the goal of multi-objective optimization for mass and displacement while ensuring the stress. Meanwhile, the optimal topology, shape and thickness optimization for the runflat structure have been achieved at the same time.