Timestamping messages and events in a distributed system using synchronous communication

Determining order relationship between events of a distributed computation is a fundamental problem in distributed systems which has applications in many areas including debugging, visualization, checkpointing and recovery. Fidge/Mattern’s vector-clock mechanism captures the order relationship using a vector of size N in a system consisting of N processes. As a result, it incurs message and space overhead of N integers. Many distributed applications use synchronous messages for communication. It is therefore natural to ask whether it is possible to reduce the timestamping overhead for such applications. In this paper, we present a new approach for timestamping messages and events of a synchronously ordered computation, that is, when processes communicate using synchronous messages. Our approach depends on decomposing edges in the communication topology into mutually disjoint edge groups such that each edge group either forms a star or a triangle. We show that, to accurately capture the order relationship between synchronous messages, it is sufficient to use one component per edge group in the vector instead of one component per process. Timestamps for events are only slightly bigger than timestamps for messages. Many common communication topologies such as ring, grid and hypercube can be decomposed into edge groups, resulting in almost 50% improvement in both space and communication overheads. We prove that the problem of computing an optimal edge decomposition of a communication topology is NP-complete in general. We also present a heuristic algorithm for computing an edge decomposition whose size is within a factor of two of the optimal. We prove that, in the worst case, it is not possible to timestamp messages of a synchronously ordered computation using a vector containing fewer than components when N ≥ 2. Finally, we show that messages in a synchronously ordered computation can always be timestamped in an offline manner using a vector of size at most . An earlier version of this paper appeared in 2002 Proceedings of the IEEE International Conference on Distributed Computing Systems (ICDCS). The author V. K. Garg was supported in part by the NSF Grants ECS-9907213, CCR-9988225, an Engineering Foundation Fellowship. This work was done while the author C. Skawratananond was a Ph.D. student at the University of Texas at Austin.     

Modeling and Managing Interactions among Business Processes

Most workflow management systems (WfMSs) only support the separate andindependent execution of business processes. However, processes often needto interact with each other, in order to synchronize the execution of theiractivities, to exchange process data, to request execution of services, orto notify progresses in process execution. Recent market trends also raisethe need for cooperation and interaction between processes executed in differentorganizations, posing additional challenges. In fact, in order to reduce costsand provide better services, companies are pushed to increase cooperation and toform virtual enterprises, where business processes span across organizationalboundaries and are composed of cooperating workflows executed in differentorganizations. Workflow interaction in a cross-organizational environment iscomplicated by the heterogeneity of workflow management platforms on top ofwhich workflows are defined and executed and by the different and possiblycompeting business policies and business goals that drive process executionin each organization.In this paper we propose a model and system that enable interactionbetween workflows executed in the same or in different organizations. Weextend traditional workflow models by allowing workflows to publish andsubscribe to events, and by enabling the definition of points in the processexecution where events should be sent or received. Event notifications aremanaged by a suitable event service that is capable of filtering andcorrelating events, and of dispatching them to the appropriate targetworkflow instances. The extended model can be easily mapped onto anyworkflow model, since event specific constructs can be specified by means ofordinary workflow activities, for which we provide the implementation. Inaddition, the event service is easily portable to different platforms, anddoes not require integration with the WfMS that supports the cooperatingworkflows. Therefore, the proposed approach is applicable in virtually anyenvironment and is independent on the specific platform adopted     

水文极限分析中改进自适应重要抽样法的应用分析

近年来,随着国内水资源的日渐紧缺,缺水问题一直是困扰我国的发展和进步,甚至已经成为了世界范围的大问题。同时,也注意到不同城市地区以及不同国家范围内受到极端水事件的各种自然灾害以及人为泄露等原因的影响也不断的增加,促使相关的水分析抽样方法在一定程度上得到了快速的发展。文章就水文极限分析中改进自适应重要抽样法的应用进行了分析和论证。     

变动态存储系数法在辽宁大凌河流域河道洪水演算中的运用研究

本文选用变动态存储系数法进行河道洪水演算,弥补传统水文模型河道洪水演算将洪水传播时间设为定值的不足。论文选取辽宁大凌河上游大城子水文站2000-2013年15场洪水资料对模型进行率定和验证,并和传统水文模型河道洪水演算方法模拟结果进行对比研究,结果表明相比于传统水文模型,采用变动态存储系数法的洪水模拟精度有所提高,15场洪水模拟合格率提高20%。研究成果对于大凌河流域水文模拟,特别是分布式水文模拟提供较为重要的参考价值。     

Arc Hydro模型提取流域水文信息及精度分析——以松花江流域为例

流域水文模型已成为流域水文信息提取的重要手段。运用Arc Hydro模型以松花江流域为研究对象,以分辨率为90 m的SRTM DEM为数据源,以松花江流域1∶25万水系矢量数据为参照,分别在400,500和600 km2三个不同集水面积阈值下进行河网提取。运用图像比对软件Alike Duplicate Image Finder对所提取河网进行精度分析。结果显示:集水面积阈值为500 km2下提取的河网最为精确。在500 km2集水面积阈值基础上,运用Arc Hydro模型将松花江流域划分为642个子流域。基于Arc Hydro模型提取的松花江流域河网与实际河网基本一致,说明利用该模型进行流域水文信息提取是合理可行的。     

Organizational Problems of Water Distribution in Khorezm,Uzbekistan

Abstract

The paper addresses problems of water resource management on the district and provincial level in the Khorezm province, Uzbekistan. The district water organizations are responsible for equitable water distribution to the agricultural users. These organizations do not have the necessary logistical capacities to manage the water resources nor to control water utilization at the local level. Over-extraction and the lack of control are leading to common pool resource problems at the district level. Furthermore, the concept of administrational management of water resources at the district level, instead of hydrological management increases the problems of equitable water distribution on the provincial, national, and international level.     

The Main Factors Affecting Isotopes of Yellow River Water in China

Abstract

Variation of δ¹⁸O, δD, and ³H in the Yellow River water were analyzed based on the isotope test results of water samples in 18 sections of the Yellow River in rainy and dry seasons. The results show the trend of the ratios of the stable isotopes increases while the ³H concentration decreases progressively from the river source to the estuary. The main factors affecting the isotopes in the river water are the mixing of foreign water bodies, evaporation, and human activities. River runoff mostly comes from the source and the middle reaches of the river. The changes of the isotopes in the river water could be served as a good indicator of the recharge of different foreign water to the Yellow River.     

基于二叉级联结构的并行极速学习机算法

为解决因庞大的矩阵存储和计算,ELM（Extreme Learning Machines）难以应用到大规模、高维数据集的问题,提出一种基于＂分而治之＂策略的并行极速学习机算法。该算法利用二叉级联结构,将大规模数据集分派到多个计算节点上,并行地更新单隐层前馈网络的输出权值,且能有限步地单调收敛到最小二乘解。实验结果表明,该算法不仅泛化性能优异,并且具有非常高的加速比和并行效率。     

白洋淀流域分布式水文模型开发与验证

针对白洋淀流域水资源保护工作开发了分布式水文模型WEP-L模型。WEP-L模型是对流域水循环过程与能量循环过程的综合模拟,具有较高的模拟精度。对白洋淀流域1956 } 2000年的径流模拟计算表明:主要水文站的相对误差在5%以内,Nash-Sutcliffe效率系数在0. 8以上,可以用于白洋淀流域的水文循环分析。     

水文模型参数的灵敏度分析

利用RSA和Sobol’两种全局灵敏度分析方法,对新安江模型中的主要产汇流参数进行了灵敏度分析,分析中采用Latin超立方采样方法,设定了模型参数的合理取值范围。参数灵敏度分析结果表明,两种方法得到的结果比较一致,流域蓄水容量是最敏感的参数,其次为汇流参数。灵敏度分析为水文模型有效的参数率定提供了技术支持。