Similarity-Based Bayesian Learning from Semi-structured Log Files for Fault Diagnosis of Web Services

Xu, Han; Shi, Zhongzhi; Niu, Wenjia; Chen, Kunrong; Yang, Xinghua

doi:10.1109/wi-iat.2010.51

Cited by 9 publications

(5 citation statements)

References 12 publications

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“…For every layer, the core code was isolated from fault tolerance component. Han [11] clustered faults based on structures of log files. These clusters were distinguished from private data set to similar data set.…”

Section: Related Workmentioning

confidence: 99%

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An Approach to Web Service Faults Diagnosis Based on Conditional Random Fields

Liu¹,

Qiu²

2017

IJCA

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Section: Related Workmentioning

confidence: 99%

“…Some are based on models [4][5][6] and others are based on historical data [7][8][9][10][11][12]. For approaches based on models, the quality of diagnosis heavily depends on the completeness of web service composition system.…”

Section: Introductionmentioning

confidence: 99%

An Approach to Web Service Faults Diagnosis Based on Conditional Random Fields

Liu¹,

Qiu²

2017

IJCA

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“…However, the system needs further investigation to improve cell data shape for user positioning purposes. H. Xu et al [6] proposed a similaritybased Bayesian learning approach to diagnosis fault. It can estimate similarity degrees of structural elements from different log files, construct Bayesian network and to compute probabilities using similarity-based learning algorithm.…”

Section: Introductionmentioning

confidence: 99%

Visualization and cell data analysis tool based on XML log files

Talukder

Andersson

Ahsan

2015

2015 IEEE 40th Local Computer Networks Conference Workshops (LCN Workshops)

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Abstract-Mobility management is an essential feature of cellular networks. High accuracy of mobile user positioning is needed to handle mobility efficiently enough and bad cell data can harm this feature significantly. Inaccuracy of cell shapes, lack of cell data measurements, and inaccurate coordination in a geographical area are major shortcomings when it comes to positioning of mobile users in cellular networks. This paper describes a tool that visualizes and analyzes cell data based on XML log files. The tool evaluates a mathematical expression to identify bad cells from the log file and successfully fixes most of the bad cells identified. The tool repairs bad cell shapes in order to achieve better positioning of mobile users.

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“…At present, there are two major methods for diagnosing service faults: the model-based (MBD) method [1][2][3][4][5][6][7][8][9][10] and process history based method [11][12][13]. MBD method models the web service composition by the behavior and function specification of service.…”

Section: Introductionmentioning

confidence: 99%

Automatic Diagnosis for Composite Web Service in Cloud Computing

Jia¹,

Chen²,

Xu³

2013

Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013)

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Abstract-Cloud computing is becoming a popular and important platform for web service applications. With the advent of more and more service resources in cloud, it is a crucial challenge to build an effective diagnostic mechanism. To improve the diagnosis capability for composite web service, we propose an automatic diagnostic framework and a hybrid diagnosis method for diagnosing the faulty activities. Our diagnostic framework can improve the scalability of diagnostic system and add the diagnostic capability of diagnosis service by decoupling the diagnostic service components. Our diagnosis method identifies the differences between successful and failed executions for finding the incorrect activities of the composite service and provides faulty causes by considering the structured activities in the process of diagnosis. Experimental results show that our method is effective to the composite web service in the fault diagnosis.

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Similarity-Based Bayesian Learning from Semi-structured Log Files for Fault Diagnosis of Web Services

Cited by 9 publications

References 12 publications

An Approach to Web Service Faults Diagnosis Based on Conditional Random Fields

An Approach to Web Service Faults Diagnosis Based on Conditional Random Fields

Visualization and cell data analysis tool based on XML log files

Automatic Diagnosis for Composite Web Service in Cloud Computing

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