一种基于开放网络的跨层模型,用于分析基于soa的信息服务

A. Kolarov, Gi Tae Kim
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引用次数: 0

摘要

基于面向服务的体系结构(SOA)的信息系统和服务在复杂的关键任务操作环境中得到了更广泛的应用。为了有效地帮助为这种复杂的操作环境设计和准备信息共享服务,设计人员必须考虑跨SOA应用程序、通信中间件和网络基础设施层的各种体系结构权衡和交互。在本文中,我们描述了一个新的建模和分析框架,用于分析和评估基于soa的信息服务的性能及其在不同网络基础设施和不同网络负载条件下的无数设计和部署选项。我们在OPNET中开发的建模框架定义了关键的有效性度量(MOEs),以考虑SOA交互特征,以及底层SOA通信中间件和网络基础设施来表征候选应用程序的性能。我们的建模框架提供了分析原有应用场景和潜在替代架构的能力,这些架构可能包括不同的应用特征(例如,应用程序数据生成速率的增加)、不同的SOA交互特征(例如,发布-订阅与请求-响应通信风格、使用JSON与XML进行数据交换、使用SAML安全令牌等)或网络特征(例如,不同的后台流量和延迟)。我们的建模框架的一个关键特性是能够发现由于应用程序层、SOA层和网络层之间不利的或不可预见的交互而导致的问题。通过公共/私有网络相互连接的跨企业机构间基础设施评估信息共享服务的初步结果证明了我们的跨层建模框架的可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
AN OPNET BASED NOVEL CROSS-LAYER MODEL FOR ANALYZING SOA-BASED INFORMATION SERVICES
Service Oriented Architecture (SOA) based information systems and services are finding wider applicability in complex, mission-critical operational environments. In order to effectively help design and prepare information sharing services for such complex operational environments, designers have to consider various architecture tradeoffs and interactions across the SOA application, communication middleware and network infrastructure layers. In this paper, we describe a novel modeling and analysis framework for analyzing and evaluating the performance of SOA-based information services and their myriad design & deployment options over varying network infrastructures under varying conditions of network load. Our modeling framework developed in OPNET defines critical Measures of Effectiveness (MOEs) to characterize performance of candidate applications considering the SOA interaction characteristics, as well as the underlying SOA communication middleware and network infrastructures. Our modeling framework provides the ability to both analyze as-is application scenarios as well as potential alternative architectures that may include differing application characteristics (e.g. increase in the application’s data generation rate), varying the SOA interaction characteristics (e.g. pub-sub vs. requestresponse communication styles, use of JSON vs. XML for data-interchange, use of SAML security tokens etc.) or network characteristics (e.g. varying background traffic and latency). A key feature of our modeling framework is the ability to uncover issues resulting from adverse or unforeseen interactions between the Application, SOA interactions and Network layers. Our initial results on evaluating Information sharing services across enterprise inter-agency infrastructures interconnected by public/private networks demonstrate the viability of our cross-layer modeling framework.
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