Cost and accuracy aware scientific workflow retrieval based on distance measure
| Autor: | Jun Wei, Yinglong Ma, Moyi Shi |
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| Rok vydání: | 2015 |
| Předmět: |
Information Systems and Management
Information retrieval Computer science Quality of service computer.software_genre Workflow engine Computer Science Applications Theoretical Computer Science Workflow technology Workflow Artificial Intelligence Control and Systems Engineering Graph (abstract data type) Data mining computer Software Workflow management system |
| Zdroj: | Information Sciences. 314:1-13 |
| ISSN: | 0020-0255 |
| DOI: | 10.1016/j.ins.2015.03.055 |
| Popis: | Scientific workflows have been applied in many scientific areas with the large amount of complex data computation tasks such as life science, astronomy and earth science, etc. However, most existing approaches for scientific workflow retrieval neglect some constraints of quality of services (QoS) that users are really concerned about, and fail to allow users to express and retrieve scientific workflows with arbitrary constraints based on graph structures of workflows. In this paper, we propose a novel approach for scientific workflow retrieval with cost constraints. We present a graph representation model called Cost Constrained Graph (CCG) for representing scientific workflows with cost constraints. A distance measure is defined for accurate workflow retrieval. The CCGs representing candidate workflows can be ranked by comparing the similarity among them. We also theoretically prove that this measure satisfies all the four properties of distance. Furthermore, we develop a prototype system for editing, assignment of weights, and automatic similarity computation of workflows. At last, the related experiments are made to demonstrate the usefulness and efficiency of workflow retrieval based on our approach. |
| Databáze: | OpenAIRE |
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