RL4CEP: reinforcement learning for updating CEP rules
Abstract This paper presents RL4CEP, a reinforcement learning (RL) approach to dynamically update complex event processing (CEP) rules. RL4CEP uses Double Deep Q-Networks to update the threshold values used by CEP rules. It is implemented using Apache Flink as a CEP engine and Apache Kafka for messa...
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| Format: | Article |
| Language: | English |
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Springer
2025-01-01
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| Series: | Complex & Intelligent Systems |
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| Online Access: | https://doi.org/10.1007/s40747-024-01742-3 |
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| author | Afef Mdhaffar Ghassen Baklouti Yassine Rebai Mohamed Jmaiel Bernd Freisleben |
| author_facet | Afef Mdhaffar Ghassen Baklouti Yassine Rebai Mohamed Jmaiel Bernd Freisleben |
| author_sort | Afef Mdhaffar |
| collection | DOAJ |
| description | Abstract This paper presents RL4CEP, a reinforcement learning (RL) approach to dynamically update complex event processing (CEP) rules. RL4CEP uses Double Deep Q-Networks to update the threshold values used by CEP rules. It is implemented using Apache Flink as a CEP engine and Apache Kafka for message distribution. RL4CEP is a generic approach for scenarios in which CEP rules need to be updated dynamically. In this paper, we use RL4CEP in a financial trading use case. Our experimental results based on three financial trading rules and eight financial datasets demonstrate the merits of RL4CEP in improving the overall profit, when compared to baseline and state-of-the-art approaches, with a reasonable consumption of resources, i.e., RAM and CPU. Finally, our experiments indicate that RL4CEP is executed quite fast compared to traditional CEP engines processing static rules. |
| format | Article |
| id | doaj-art-69ef11e2b0da4a6394a6c40349bb8ee1 |
| institution | Kabale University |
| issn | 2199-4536 2198-6053 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Springer |
| record_format | Article |
| series | Complex & Intelligent Systems |
| spelling | doaj-art-69ef11e2b0da4a6394a6c40349bb8ee12025-02-09T13:01:11ZengSpringerComplex & Intelligent Systems2199-45362198-60532025-01-0111211510.1007/s40747-024-01742-3RL4CEP: reinforcement learning for updating CEP rulesAfef Mdhaffar0Ghassen Baklouti1Yassine Rebai2Mohamed Jmaiel3Bernd Freisleben4ReDCAD Laboratory, ENIS, University of SfaxReDCAD Laboratory, ENIS, University of SfaxDepartment of Computer Science, TELNET HoldingReDCAD Laboratory, ENIS, University of SfaxDepartment of Mathematics and Computer Science, University of MarburgAbstract This paper presents RL4CEP, a reinforcement learning (RL) approach to dynamically update complex event processing (CEP) rules. RL4CEP uses Double Deep Q-Networks to update the threshold values used by CEP rules. It is implemented using Apache Flink as a CEP engine and Apache Kafka for message distribution. RL4CEP is a generic approach for scenarios in which CEP rules need to be updated dynamically. In this paper, we use RL4CEP in a financial trading use case. Our experimental results based on three financial trading rules and eight financial datasets demonstrate the merits of RL4CEP in improving the overall profit, when compared to baseline and state-of-the-art approaches, with a reasonable consumption of resources, i.e., RAM and CPU. Finally, our experiments indicate that RL4CEP is executed quite fast compared to traditional CEP engines processing static rules.https://doi.org/10.1007/s40747-024-01742-3Deep Reinforcement LearningComplex Event ProcessingFinancial TradingCEP RulesRule Updates |
| spellingShingle | Afef Mdhaffar Ghassen Baklouti Yassine Rebai Mohamed Jmaiel Bernd Freisleben RL4CEP: reinforcement learning for updating CEP rules Complex & Intelligent Systems Deep Reinforcement Learning Complex Event Processing Financial Trading CEP Rules Rule Updates |
| title | RL4CEP: reinforcement learning for updating CEP rules |
| title_full | RL4CEP: reinforcement learning for updating CEP rules |
| title_fullStr | RL4CEP: reinforcement learning for updating CEP rules |
| title_full_unstemmed | RL4CEP: reinforcement learning for updating CEP rules |
| title_short | RL4CEP: reinforcement learning for updating CEP rules |
| title_sort | rl4cep reinforcement learning for updating cep rules |
| topic | Deep Reinforcement Learning Complex Event Processing Financial Trading CEP Rules Rule Updates |
| url | https://doi.org/10.1007/s40747-024-01742-3 |
| work_keys_str_mv | AT afefmdhaffar rl4cepreinforcementlearningforupdatingceprules AT ghassenbaklouti rl4cepreinforcementlearningforupdatingceprules AT yassinerebai rl4cepreinforcementlearningforupdatingceprules AT mohamedjmaiel rl4cepreinforcementlearningforupdatingceprules AT berndfreisleben rl4cepreinforcementlearningforupdatingceprules |