FENECIA: failure endurable nested-transaction based execution of composite Web services with incorporated state analysis

Interest in the Web services (WS) composition (WSC) paradigm is increasing tremendously. A real shift in distributed computing history is expected to occur when the dream of implementing Service-Oriented Architecture (SOA) is realized. However, there is a long way to go to achieve such an ambitious goal. In this paper, we support the idea that, when challenging the WSC issue, the earlier that the inevitability of failures is recognized and proper failure-handling mechanisms are defined, from the very early stage of the composite WS (CWS) specification, the greater are the chances of achieving a significant gain in dependability. To formalize this vision, we present the FENECIA (Failure Endurable Nested-transaction based Execution of Composite Web services with Incorporated state Analysis) framework. Our framework approaches the WSC issue from different points of view to guarantee a high level of dependability. In particular, it aims at being simultaneously a failure-handling-devoted CWS specification, execution, and quality of service (QoS) assessment approach. In the first section of our framework, we focus on answering the need for a specification model tailored for the WS architecture. To this end, we introduce WS-SAGAS, a new transaction model. WS-SAGAS introduces key concepts that are not part of the WS architecture pillars, namely, arbitrary nesting, state, vitality degree, and compensation, to specify failure-endurable CWS as a hierarchy of recursively nested transactions. In addition, to define the CWS execution semantics, without suffering from the hindrance of an XML-based notation, we describe a textual notation that describes a WSC in terms of definition rules, composability rules, and ordering rules, and we introduce graphical and formal notations. These rules provide the solid foundation needed to formulate the execution semantics of a CWS in terms of execution correctness verification dependencies. To ensure dependable execution of the CWS, we present in the second section of FENECIA our architecture THROWS, in which the execution control of the resulting CWS is distributed among engines, discovered dynamically, that communicate in a peer-to-peer fashion. A dependable execution is guaranteed in THROWS by keeping track of the execution progress of a CWS and by enforcing forward and backward recovery. We concentrate in the third section of our approach on showing how the failure consideration is trivial in acquiring more accurate CWS QoS estimations. We propose a model that assesses several QoS properties of CWS, which are specified as WS-SAGAS transactions and executed in THROWS. We validate our proposal and show its feasibility and broad applicability by describing an implemented prototype and a case study.     

Using visual and text features for direct marketing on multimedia messaging services domain

Traditionally, direct marketing companies have relied on pre-testing to select the best offers to send to their audience. Companies systematically dispatch the offers under consideration to a limited sample of potential buyers, rank them with respect to their performance and, based on this ranking, decide which offers to send to the wider population. Though this pre-testing process is simple and widely used, recently the industry has been under increased pressure to further optimize learning, in particular when facing severe time and learning space constraints. The main contribution of the present work is to demonstrate that direct marketing firms can exploit the information on visual content to optimize the learning phase. This paper proposes a two-phase learning strategy based on a cascade of regression methods that takes advantage of the visual and text features to improve and accelerate the learning process. Experiments in the domain of a commercial Multimedia Messaging Service (MMS) show the effectiveness of the proposed methods and a significant improvement over traditional learning techniques. The proposed approach can be used in any multimedia direct marketing domain in which offers comprise both a visual and text component.

基于SOA的空间信息资源整合与服务模式探讨

提高空间信息资源的整合与服务水平,在迈向信息和服务型社会的过程中具有十分重要的意义。文章根据作者近年来在该领域的相关应用研究,对空间信息资源整合与服务模式进行了探讨,总结了基于SOA实现空间信息资源整合与服务的模式,并通过实例阐述了空间信息资源整合与服务的组织、实施和应用。     

基于多类别支持向量机的城市交通网络模式分类研究

在网络层次上进行区域交通信号控制、交通分配和路径诱导是缓解交通堵塞的有效途径之一。为进一步提高城市交通网络分类检测的准确性,将支持向量机（Support Vector Machine）应用于交通事件的模式分类研究。通过提出一种基于多类别支持向量机的交通模式分类方法,设计了适合该检测系统的网络结构。仿真结果表明：相对于其他算法,城市交通网络的状态可分为数量有限且不同类型的模式,并且这些模式不断重复出现,当系统识别出网络处于某种模式时,就可参照事先确定的优化参数及策略进行交通控制和诱导,以缓解交通拥塞,提高交通系统的运行效率。该网络结构对于小样本数据具有检测率高、误报率低的优点,完全适用于城市交通的模式分类,同时也存在不足之处,指出了今后进一步研究的方向。     

基于位置矩阵QoS感知的Web服务组合研究

提出了一种基于位置矩阵QoS感知的Web服务组合方法。该方法使用遗传算法用位置矩阵对基因进行编码,使得该编码方式可以表示服务组合的所有组合路径和重计划信息,算法的一次执行就能完成所有路径QoS最优的全局搜索和动态重计划功能。实验结果证明了该方法的有效性和可行性。     

校园网Web服务器的安全配置及防范对策

随着网络技术的快速发展,校园网Web服务器的安全越来越受到人们的重视,该文从Windows Server 2003操作系统、IIS6、ASP.NET和SQL Server 2000数据库管理系统等多方面详细阐述了校园网Web服务器的安全配置,并提出了一些防范对策。     

基于SOA的数据业务服务总线的研究设计

各种数据业务平台在功能和实现方面有较多相似之处.本文在SOA(Service-Oriented Architecture,面向服务的体系结构)思想基础上,研究设计了数据业务服务总线框架,并分析了该框架的安全性和通信性能.该框架通过Web Services技术实现了软总线结构的消息中间件,提供了业务逻辑的灵活加载、消息流量控制和与传输协议无关等特性.     

基于MDA的Web服务组合的研究及应用

随着已有Web服务数量的不断增加,如何利用这些现有的Web服务创建新的更复杂的Web服务成为一项新的研究课题。特别地,利用MDA进行Web服务合成已经成为研究的热点。提出了一种基于模型驱动架构的Web服务组合方法,将模型驱动软件开发方法学应用到Web服务组合中。针对WSDL语言给出了一个UML Profile for WSDL来建立与WSDL平台相关的静态结构模型,并给出了与WSDL平台相关的静态结构模型和WSDL语言之间的模型转化规则。并通过一个旅行代理服务的实例说明了方法的应用情况,验证了方法的可行性。     

An economic input-output analysis for urban stormwater quality planning

A new approach using input-output techniques is proposed for the analysis of urban stormwater pollution caused by urban land development. The input-output model provides projections of sectoral outputs within an urban region. By defining land as an input to production, these output projections may be translated into projections of commercial and industrial land development. Furthermore, the closed version of the input-output model is used to project residential land development as a function of projected wage income. The pollutant generation in urban stormwater is related to the quantity of each category of land development by a pollutant coefficient matrix. Thus, the model can be used to predict the impact of various economic growth scenarios on pollution loadings in runoff water. This will help planners in assessing the environmental costs of various scenarios, and in preparing for remedial actions. A numerical example is provided to illustrate the applications of the model.     

Hybrid Metaheuristics Web Service Composition Model for QoS Aware Services

Recent advancements in cloud computing (CC) technologies signified that several distinct web services are presently developed and exist at the cloud data centre. Currently, web service composition gains maximum attention among researchers due to its significance in real-time applications. Quality of Service (QoS) aware service composition concerned regarding the election of candidate services with the maximization of the whole QoS. But these models have failed to handle the uncertainties of QoS. The resulting QoS of composite service identified by the clients become unstable and subject to risks of failing composition by end-users. On the other hand, trip planning is an essential technique in supporting digital map services. It aims to determine a set of location based services (LBS) which cover all client intended activities quantified in the query. But the available web service composition solutions do not consider the complicated spatio-temporal features. For resolving this issue, this study develops a new hybridization of the firefly optimization algorithm with fuzzy logic based web service composition model (F3L-WSCM) in a cloud environment for location awareness. The presented F3L-WSCM model involves a discovery module which enables the client to provide a query related to trip planning such as flight booking, hotels, car rentals, etc. At the next stage, the firefly algorithm is applied to generate composition plans to minimize the number of composition plans. Followed by, the fuzzy subtractive clustering (FSC) will select the best composition plan from the available composite plans. Besides, the presented F3L-WSCM model involves four input QoS parameters namely service cost, service availability, service response time, and user rating. An extensive experimental analysis takes place on CloudSim tool and exhibit the superior performance of the presented F3L-WSCM model in terms of accuracy, execution time, and efficiency.