SWORD: scalable and flexible workload generator for distributed data processing systems
Proceedings of the 38th conference on Winter simulation
Employing Latent Dirichlet Allocation for fraud detection in telecommunications
Pattern Recognition Letters
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
SPADE: the system s declarative stream processing engine
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Distributed multi-layered workload synthesis for testing stream processing systems
Proceedings of the 40th Conference on Winter Simulation
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Billing Mediation Platform (BMP) in Telco is used to process real-time streams of Call Detail Records (CDRs) which can number tens of billions a day. The comprehensive records generated by BMPs can be used for billing and accounting, fraud detection, campaign management, spam filtering, traffic analysis, and churn prediction. Many of these applications are characterized by real-time processing requiring high throughput, low-latency analysis of CDRs. Testing such BMPs has different dimensions, stress testing of analytics for scalability, correctness of analytics, what-if scenarios, all of which require CDRs with realistic volumetric and contextual properties. We propose WLG, a framework for testing and benchmarking BMPs which involves generating high volumes of CDRs representative of real-world data. The framework is flexible in its ability to express and tune the workload generation to simulate CDRs from broad range of traffic patterns while preserving different spatio-temporal correlations and content-level information observed in real-world CDRs.