In this paper, clustering of scientific workflows is investigated. It proposes a work to encode workflows through workflow representations as sets of embedded workflows. Then, it embeds extracted workflow motifs in sets of workflows. By motifs, common patterns of workflow steps and relationships are replaced with indices. Motifs are defined as small functional units that occur much more frequently than expected. They can show hidden relationships, and they keep as much underlying information as possible. In order to have a good estimate on distances between observed workflows, this work proposes the scientific workflow clustering problem with exploiting set descriptors, instead of vector based descriptors. It uses k-means algorithm as a popular clustering algorithm for workflow clustering. However, one of the biggest limitations of the k-means algorithm is the requirement of the number of clusters, K, to be specified before the algorithm is applied. To address this problem it proposes a method based on the SFLA. The simulation results show that the proposed method is better than PSO and GA algorithms in the K selection.
Ubiquitous computing is a concept in engineering where the computing is made to appear anytime and everywhere. This paradigm is also described as pervasive computing, or ambient intelligence. Considering ubiquitous computing perspectives can be useful to manage workflows, because running workflows usually needs large-scale computing resources and massive storages [1] and considering the relatedness between data. Ubicomp is a concept in engineering where the computing is made to appear anytime and everywhere. This paradigm is also described as pervasive computing, or ambient intelligence. Figure 1 represents Big Data challenges in workflow management systems (WfMSs). By creating workflows, skilled and non-skilled designers can manage and control their tasks. It is necessary to gather all the data and to consider various aspects of information in the design of a clear and helpful workflow, unless the workflow might cusses destructive effects on experiment or activities. Therefore, the WfMSs
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