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SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
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ASN.1: communication between heterogeneous systems
ASN.1: communication between heterogeneous systems
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IEEE Transactions on Knowledge and Data Engineering
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GPCE '02 Proceedings of the 1st ACM SIGPLAN/SIGSOFT conference on Generative Programming and Component Engineering
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SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
PADS: a domain-specific language for processing ad hoc data
Proceedings of the 2005 ACM SIGPLAN conference on Programming language design and implementation
Adaptive information extraction
ACM Computing Surveys (CSUR)
Adaptable Parsing of Real-Time Data Streams
PDP '07 Proceedings of the 15th Euromicro International Conference on Parallel, Distributed and Network-Based Processing
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ICAI'09 Proceedings of the 10th WSEAS international conference on Automation & information
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SAFECOMP'12 Proceedings of the 2012 international conference on Computer Safety, Reliability, and Security
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Dependable (i.e. accurate and timely) monitoring is a key aspect of business process management, since it provides information which is crucial for determining the actual Quality of Service (QoS) delivered to individual parties, and for promptly handling off-plan deviations. This paper describes a business process monitor for the recharging system of a mobile phone network provider. The monitored system is currently in operation for the major mobile phone company in Italy, namely Telecom Italia Mobile (TIM). Due to the amazingly high throughput of the monitored system, meeting the performance requirements for the monitor was a challenging issue. A buffer-based implementation of the monitor system failed to meet such requirements. In this paper, we propose a stream-based architecture, which exceeds the performance requirements imposed by the monitored application. The paper provides a detailed description of the monitor system architecture, including a discussion of technology choices, and an experimental evaluation of the performance boost achieved by resorting to a streaming approach. The proposed solution also exploits grammar-based pluggable parsers for rapid and seamless integration of heterogeneous data feeds.