Run-based exception prediction for workflows

Si, Yain-Whar; Hoi, Kin Kuan; Biuk-Aghai, Robert P.; Fong, Simon; Zhang, Defu

doi:10.1016/j.jss.2015.11.024

Cited by 4 publications

(3 citation statements)

References 8 publications

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“…A run consists of all or a subset of nodes and edges within a workflow schema beginning from the start node to the end node [9,33] . Detailed discussion of about the runs and relevant examples can be found in [34]. Second, we unfold the BPMN models based on the probability-based unfolding algorithms.…”

Section: Methodsmentioning

confidence: 99%

Unraveling Iterative Control Structures from Business Processes

Si¹,

Yung²

2021

J. Comput. Sci. Technol.

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Iterative control structures allow the repeated execution of tasks, activities or sub-processes according to the given conditions in a process model. Iterative control structures can significantly increase the risk of triggering temporal exceptions since activities within the scope of these control structures could be repeatedly executed until a predefined condition is met. In this paper, we propose two approaches to unravel iterative control structures from process models. The first approach unravels loops based on zero-one principle. The second approach unravels loops based on branching probabilities assigned at split gateways. The proposed methods can be used to unfold structured loops, nested loops and crossing loops. Since the unfolded model does not contain any iterative control structures, it can be used for further analysis by process designers during the modeling phase. The proposed methods are implemented based on workflow graphs, and therefore they are compatible with modeling languages such as Business Process Modelling Notation (BPMN). In the experiments, the execution behavior of unfolded process models is compared against the original models based on the concept of runs. Experimental results reveal that runs generated from the original models can be correctly executed in the unfolded BPMN models that do not contain any loops.

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Section: Methodsmentioning

confidence: 99%

Unraveling Iterative Control Structures from Business Processes

Si¹,

Yung²

2021

J. Comput. Sci. Technol.

Self Cite

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“…Em [Bala and Chana 2015] Bala desenvolveu um trabalho semelhante, no entanto usou técnicas de aprendizado diferentes: Naive Bayes, Regressão Logística, Redes Neurais Artificiais e Random Forest. Em [Si et al 2016],é proposto um algoritmo de predição temporal de exceções onde as predições são baseados no estado de execução do workflow.…”

Section: Trabalhos Relacionadosunclassified

Predição de Falhas em Workflows Científicos em Nuvens baseada em Aprendizado de Máquina

Silva¹,

Paes²,

Oliveira³

2017

Anais Do XI Brazilian E-Science Workshop (BRESCI 2017)

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Os cientistas cada vez mais têm se apoiado em ferramentas computacionais para executar e analisar experimentos científicos, almejando reduzir esforços e custos para comprovar ou refutar hipóteses. Entretanto, recursos podem ser desperdiçados se os parâmetros usados nas aplicações fizerem com que a execução do experimento falhe. Assim, para diminuir a quantidade de execuções que resultam em falha, este artigo propõe a integração de uma técnica de Aprendizado de Máquina com um Sistema de Gerência de Workflows Científicos para induzir um modelo preditivo de falhas, a partir de dados de proveniência. Resultados experimentais mostram que o modelo é capaz de identificar corretamente casos de falha no Workflow Científico SciPhy.

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“…Si Y. W. [6] proposed a run-based exception prediction algorithm to predict temporal exceptions in workflows. The proposed algorithm is divided into two phases, design-time and run time.…”

Section: Introductionmentioning

confidence: 99%

Research on Exception of Meteorological Satellite Ground System Application Based on Resource Bottleneck

Zhao¹,

Lin²,

Lin³

et al. 2017

ACS

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Meteorological satellite ground application system resources are limited. Abnormal satellite missions often lead to hopple of system resources. In order to analyze the problem, this paper presents an anomaly analysis method for meteorological satellite ground system based on resource bottleneck. Through the CPU, memory and I/O, several types of resources in-depth were analyzed to find the bottleneck caused by the problem, thus providing recommendations for application optimization. Experimental analysis shows that the proposed method can reasonably analyze the resource bottleneck of CPU, memory and I/ O, and draw a good conclusion. To solve the meteorological satellite application system application anomaly caused by the bottleneck of the problem, the application of optimization to a certain extent plays a positive role.

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Run-based exception prediction for workflows

Cited by 4 publications

References 8 publications

Unraveling Iterative Control Structures from Business Processes

Unraveling Iterative Control Structures from Business Processes

Predição de Falhas em Workflows Científicos em Nuvens baseada em Aprendizado de Máquina

Research on Exception of Meteorological Satellite Ground System Application Based on Resource Bottleneck

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