Real-time Stream-based Monitoring
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Abstract (arXiv)
We introduce RTLola, a new stream-based specification language for the description of real-time properties of reactive systems. The key feature is the integration of sliding windows over real-time intervals with aggregation functions into the language. Using sliding windows we can detach fixed-rate output streams from the varying rate input streams. We provide an efficient evaluation algorithm of the sliding windows by partitioning the windows into intervals according to a given monitor frequency. For useful aggregation functions, the intervals allow a more efficient way to compute the aggregation value by dynamically reusing interval summaries. In general, the number of input values within a single window instance can grow arbitrarily large disallowing any guarantees on the expected memory consumption. Assuming a fixed monitor output rate, we can provide memory guarantees which can be computed a-priori. Additionally, for specifications using certain classes of aggregation functions, we can perform a more precise, better memory analysis. We demonstrate the applicability of the new language on practical examples.
Key facts. Cited by 13 papers in the map (data through 14 Oct 2026). First posted on arXiv 10 Nov 2017.
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Citing papers per year: 2021: 3; 2022: 4; 2023: 3; 2024: 0; 2025: 2; 2026: 1.
13 papers.
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- 2023Monitoring Algorithmic Fairnesscited by 8
- 2023Monitoring Algorithmic Fairness under Partial Observationscited by 7
- 2021SINGA-Easy: An Easy-to-Use Framework for MultiModal Analysiscited by 0
- 2021VisualTextRank: Unsupervised Graph-based Content Extraction for Automating Ad Text to Image Searchcited by 0
- 2021Text is NOT Enough: Integrating Visual Impressions into Open-domain Dialogue Generationcited by 0
- 2022Discovering Personalized Semantics for Soft Attributes in Recommender Systems using Concept Activation Vectorscited by 0
- 2022Reinforced MOOCs Concept Recommendation in Heterogeneous Information Networkscited by 0
- 2022Explanation-Guided Fairness Testing through Genetic Algorithmcited by 0
- 2022Using Graph Neural Networks for Program Terminationcited by 0
- 2023Tribe or Not? Critical Inspection of Group Differences Using TribalGramcited by 0
- 2025Monitoring of Static Fairnesscited by 0
- 2025Algorithmic Fairness: A Runtime Perspectivecited by 0
1 more
- 2026Energy Shields for Fairnesscited by 0
- 2026Energy Shields for Fairness24 May 2026
- 2025Algorithmic Fairness: A Runtime Perspective28 Jul 2025
- 2025Monitoring of Static Fairness3 Jul 2025
- 2023Monitoring Algorithmic Fairness under Partial Observations1 Aug 2023
- 2023Monitoring Algorithmic Fairness25 May 2023
- 2023Tribe or Not? Critical Inspection of Group Differences Using TribalGram16 Mar 2023
- 2022Using Graph Neural Networks for Program Termination28 Jul 2022
- 2022Explanation-Guided Fairness Testing through Genetic Algorithm16 May 2022
- 2022Reinforced MOOCs Concept Recommendation in Heterogeneous Information Networks8 Mar 2022
- 2022Discovering Personalized Semantics for Soft Attributes in Recommender Systems using Concept Activation Vectors6 Feb 2022
- 2021Text is NOT Enough: Integrating Visual Impressions into Open-domain Dialogue Generation13 Sep 2021
- 2021VisualTextRank: Unsupervised Graph-based Content Extraction for Automating Ad Text to Image Search5 Aug 2021
1 more
- 2023Monitoring Algorithmic Fairnesscited by 8
- 2023Monitoring Algorithmic Fairness under Partial Observationscited by 7
- 2021SINGA-Easy: An Easy-to-Use Framework for MultiModal Analysiscited by 0
- 2021VisualTextRank: Unsupervised Graph-based Content Extraction for Automating Ad Text to Image Searchcited by 0
- 2021Text is NOT Enough: Integrating Visual Impressions into Open-domain Dialogue Generationcited by 0
- 2022Discovering Personalized Semantics for Soft Attributes in Recommender Systems using Concept Activation Vectorscited by 0
- 2022Reinforced MOOCs Concept Recommendation in Heterogeneous Information Networkscited by 0
- 2022Explanation-Guided Fairness Testing through Genetic Algorithmcited by 0
- 2022Using Graph Neural Networks for Program Terminationcited by 0
- 2023Tribe or Not? Critical Inspection of Group Differences Using TribalGramcited by 0
- 2025Monitoring of Static Fairnesscited by 0
- 2025Algorithmic Fairness: A Runtime Perspectivecited by 0
12 most cited of 13 All 13 (JSON)
- 2026Energy Shields for Fairness24 May 2026
- 2025Algorithmic Fairness: A Runtime Perspective28 Jul 2025
- 2025Monitoring of Static Fairness3 Jul 2025
- 2023Monitoring Algorithmic Fairness under Partial Observations1 Aug 2023
- 2023Monitoring Algorithmic Fairness25 May 2023
- 2023Tribe or Not? Critical Inspection of Group Differences Using TribalGram16 Mar 2023
- 2022Using Graph Neural Networks for Program Termination28 Jul 2022
- 2022Explanation-Guided Fairness Testing through Genetic Algorithm16 May 2022
- 2022Reinforced MOOCs Concept Recommendation in Heterogeneous Information Networks8 Mar 2022
- 2022Discovering Personalized Semantics for Soft Attributes in Recommender Systems using Concept Activation Vectors6 Feb 2022
- 2021Text is NOT Enough: Integrating Visual Impressions into Open-domain Dialogue Generation13 Sep 2021
- 2021VisualTextRank: Unsupervised Graph-based Content Extraction for Automating Ad Text to Image Search5 Aug 2021
12 newest of 13 All 13 (JSON)