کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
378762 659215 2014 27 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Role network model-based support for RESTful business processes
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Role network model-based support for RESTful business processes
چکیده انگلیسی


• Rule support for Web-based process fragments and orchestration
• Deontic logic as indicators of obligations and permissions within process fragments
• Improved system adaption for Web-based business process orchestration
• Automatic generation of process fragments from process models and rules

The WWW is increasingly used for process-intensive business scenarios that connect services and applications together. Imperative programming and centralised traditional workflow engines lack the flexibility to support such distributed systems. RESTful business process (RESTfulBP) is an architectural style that introduces a set of constraints and uses process fragments to enable process coordination and choices at the endpoints to improve system adaptability, especially for human-intensive Web-based business processes. However, the original solution had two limitations: 1) the endpoint process fragments cannot distinguish between obligation and permission semantics to communicate richer choices of next-steps, and 2) it was time-consuming to create process fragment variants in an imperative style (either using complex workflow models or manually). In this paper, we propose a rule-based approach using the Role Network Model (RNM) to address these limitations. We introduce deontic logic into a process fragment and enable declarative generation of process fragments from rules. The proposed solution is evaluated in a real-world property valuation application using the B2B standard process from the Australian lending industry. The evaluation indicates that the new approach has improved both the design and runtime adaptability of the resulting system. Through surveys of other users employing our approach, it further demonstrates improved expressiveness, usability and general usefulness.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Data & Knowledge Engineering - Volume 94, Part A, November 2014, Pages 38–64
نویسندگان
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