Decomposing the Service Composition Problem

Zachary J. Oster, Ganesh Ram Santhanam, Samik Basu
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引用次数: 9

Abstract

Many approaches to the Web service composition problem benefit from their use of formal methods to guarantee the correctness of the composite services that they produce, but these approaches often require the functionality of the composite service to be specified using one particular formalism (e.g., goal graphs, temporal logic, pre-/post-conditions). As a result, each of these existing approaches falls short in realizing a composite service when the required functionality cannot be fully expressed in the supported formalism. To overcome this problem, we propose a new formal meta-framework that (a) is capable of reusing any existing formalisms and (b) allows the use of functional requirements that are currently not expressible in any one formalism. Our technique assumes that any functional requirement can be decomposed and expressed as a boolean combination of "atomic" requirements, which are representable in at least one existing formalism. Based on this assumption, we use existing methods to identify sets of Web services that conform to the atomic requirements. Our meta-framework then identifies compositions that conform to the overall functional requirement by (a) employing satisfiability techniques to prune the (exponentially large) space of possible compositions and (b) building workable compositions from satisfiable sets of services. As a result, our meta-framework allows for easy and effective memorization of prior composition results, thereby enhancing the efficiency of generating new compositions.
分解服务组合问题
许多解决Web服务组合问题的方法都得益于使用形式化方法来保证它们生成的组合服务的正确性,但是这些方法通常需要使用一种特定的形式化方法来指定组合服务的功能(例如,目标图、时间逻辑、前置/后用条件)。因此,当所需的功能不能以所支持的形式完全表达时,这些现有方法中的每一种都无法实现组合服务。为了克服这个问题,我们提出了一个新的正式元框架,它(a)能够重用任何现有的形式主义,(b)允许使用目前无法用任何一种形式主义表达的功能需求。我们的技术假设任何功能需求都可以分解并表示为“原子”需求的布尔组合,这些需求至少可以用一种现有的形式表示。基于这个假设,我们使用现有的方法来标识符合原子需求的Web服务集。然后,我们的元框架通过以下方式确定符合整体功能需求的组合:(a)采用可满足性技术来精简可能组合的(指数级大的)空间;(b)从可满足的服务集构建可行的组合。因此,我们的元框架允许轻松有效地记忆先前的作文结果,从而提高生成新作文的效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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