A Rule Markup Language and Its Application to UML

Jacob, Joost

doi:10.1007/11925040_3

Cited by 2 publications

(1 citation statement)

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“…Continuing with our approach to represent the structure of objects in XML format along with expanding their attributes, we want to define a standard form for selecting, filtering and aggregating objects using a Rule Markup Language (RML) tool [10,18]. RML was designed for ease of use to write patterns that match certain elements in an XML file and apply transformation rules to the file to produce a desired output.…”

Section: Introductionmentioning

confidence: 99%

A formal method for rule analysis and validation in distributed data aggregation service

Serbanescu¹,

Pop²,

Cristea³

et al. 2015

World Wide Web

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The usage of Cloud Serviced has increased rapidly in the last years. Data management systems, behind any Cloud Service, are a major concern when it comes to scalability, flexibility and reliability due to being implemented in a distributed way. A Distributed Data Aggregation Service relying on a storage system meets these demands and serves as a repository back-end for complex analysis and automatic mining of any type of data. In this paper we continue our previous work on data management in Cloud storage. We present a formal approach to express retrieval and aggregation rules with a compact, yet powerful tool called Rule Markup Language. Our extended solution proposes a standard form to schemes and uses the tool to match the rules to the XML form of the structured data in order to obtain the unstructured entries from BlobSeer data storage system. This allows the Distributed Data Aggregation Service (DDAS) to bypass several steps when processing a retrieval request. Our new architecture is more loosely-coupled with a separate module, the new tool, used for transforming the XML entries to standard XML files which represent the final result. We model the dynamic behavior of the system using this new standard to ensure a simpler and efficient representation of the operations performed by the client while maintaining the constraints imposed by a distributed system running in the Cloud. Furthermore we prove that this method correctly performs the translation between the storage model's unstructured view of data and the client's structured objects.

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Section: Introductionmentioning

confidence: 99%