- (Zhang et al., 2009) ⇒ Xiangliang Zhang, Cyril Furtlehner, Julien Perez, Cecile Germain-Renaud, and Michèle Sebag. (2009). “Toward Autonomic Grids: Analyzing the Job Flow with Affinity Streaming.” In: Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2009). doi:10.1145/1557019.1557126
- Categories and Subject Descriptors: H.2.8 Database Management: Database Applications — Data Mining; I.5.3 Pattern Recognition: Clustering — Algorithms, Similarity measures
- General Terms: Algorithms, Experimentation.
The Affinity Propagation (AP) clustering algorithm proposed by Frey and Dueck (2007) provides an understandable, nearly optimal summary of a dataset, albeit with quadratic computational complexity. This paper, motivated by Autonomic Computing, extends AP to the data streaming framework. Firstly a hierarchical strategy is used to reduce the complexity to O(N1+e) the distortion loss incurred is analyzed in relation with the dimension of the data items. Secondly, a coupling with a change detection test is used to cope with non-stationary data distribution, and rebuild the model as needed. The presented approach StrAP is applied to the stream of jobs submitted to the EGEE Grid, providing an understandable description of the job flow and enabling the system administrator to spot online some sources of failures.
|2009 TowardAutonomicGridsAnalyzingth||Xiangliang Zhang|
|Toward Autonomic Grids: Analyzing the Job Flow with Affinity Streaming||KDD-2009 Proceedings||10.1145/1557019.1557126||2009|
|Author||Xiangliang Zhang +, Cyril Furtlehner +, Julien Perez +, Cecile Germain-Renaud + and Michèle Sebag +|
|journal||Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining +|
|title||Toward Autonomic Grids: Analyzing the Job Flow with Affinity Streaming +|