The DOI matches its Crossref record; 22 of the 22 references it cites were found in a registry or an index.
A basic model for proactive event-driven computing
Abstract
During the movie "Source Code" there is a shift in the plot; from (initially) reacting to a train explosion that already occurred and trying to eliminate further explosions, to (later) changing the reality to avoid the original train explosion. Whereas changing the history after events have happened is still within the science fiction domain, changing the reality to avoid events that have not happened yet is, in many cases, feasible, and may yield significant benefits. We use the term proactive behavior to designate the change of what will be reality in the future. In particular, we focus on proactive event-driven computing: the use of event-driven systems to predict future events and react to them before they occur. In this paper we start our investigation of this large area by constructing a model and end-to-end implementation of a restricted subset of basic proactive applications that is trying to eliminate a single forecasted event, selecting between a finite and relatively small set of feasible actions, known at design time, based on quantified cost functions over time. After laying out the model, we describe the extensions required of the conceptual architecture of event processing to support such applications: supporting proactive agents as part of the model, supporting the derivation of forecasted events, and supporting various aspects of uncertainty; next, we show a decision algorithm that selects among the alternatives. We demonstrate the approach by implementing an…
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“As we mentioned in Sections 1 and 2, prescriptive analytics takes as input the outcome of predictive analytics algorithms.”
From Prescriptive analytics: Literature review and research challenges (2020) · cites this paper as Engel, Etzion, & Feldman, 2012
In the citing paper
“during the last years, there have been some attempts for coupling probabilistic logic and uncertainty into CEP engines in order to react to predictions about future events before they occur (Cugola, Margara, Matteucci, & Tamburrelli, 2015;Engel et al., 2012;Lee & Jung, 2017;Mousheimish, Taher, & Zeitouni, 2016;Wang, Cao, & Zhang, 2013).”
From Prescriptive analytics: Literature review and research challenges (2020) · cites this paper as Engel et al., 2012
Citations
Cites
A review on machinery diagnostics and prognostics implementing condition-based maintenance
Jardine, A. K. S., Lin, D., & Banjević, D. (2005) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2005.09.012 · Cited by 4,861
Statistical Methods for Survival Data Analysis.
Lachenbruch, P. A., & Lee, E. T. (1993) · Journal of the American Statistical Association · doi:10.2307/2290742 · Cited by 2,851
The Power of Events: An Introduction to Complex Event Processing in Distributed Enterprise Systems
Luckham, D. C. (2008) · Lecture notes in computer science · doi:10.1007/978-3-540-88808-6_2 · Cited by 1,299
Reiter, R. (1978) · Springer eBooks · doi:10.1007/978-1-4684-3384-5_3 · Cited by 1,129
Decision-Theoretic Planning: Structural Assumptions and Computational Leverage
Boutilier, C. E., Dean, T., & Hanks, S. (1999) · Journal of Artificial Intelligence Research · doi:10.1613/jair.575 · Cited by 1,103
Statistical Methods for Survival Data Analysis
Lee, E. T., & Wang, J. W. (2003) · Wiley series in probability and statistics · doi:10.1002/0471458546 · Cited by 1,099
Inferring Internet denial-of-service activity
Moore, D., Shannon, C., Brown, D. J., Voelker, G. M., & Savage, S. (2006) · ACM Transactions on Computer Systems · doi:10.1145/1132026.1132027 · Cited by 783
Etzion, O., & Niblett, P. (2010) · Cited by 630
Self-citationTennenhouse, D. L. (2000) · Communications of the ACM · doi:10.1145/332833.332837 · Cited by 475
Comparing autonomic and proactive computing
Want, R., Pering, T., & Tennenhouse, D. L. (2003) · IBM Systems Journal · doi:10.1147/sj.421.0129 · Cited by 109
Research works printed but not linked: 1
- SK Sethiya . Condition based maintenance (cbm) . 2006 . SK Sethiya. Condition based maintenance (cbm). 2006.
Cited by
Prescriptive analytics: Literature review and research challenges
Lepenioti, K., Bousdekis, A., Apostolou, D., & Mentzas, G. (2020) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2019.04.003 · Cited by 501
“…attempts for coupling probabilistic logic and uncertainty into CEP engines in order to react to predictions about future events before they occur (Cugola, Margara, Matteucci, & Tamburrelli, 2015; Engel et al., 2012; Lee & Jung, 2017; Mousheimish, Taher, & Zeitouni, 2016; Wang, Cao, & Zhang, 2013).”
Autonomous, context-aware, adaptive Digital Twins—State of the art and roadmap
Hribernik, K., Cabri, G., Mandreoli, F., & Mentzas, G. N. (2021) · Computers in Industry · doi:10.1016/j.compind.2021.103508 · Cited by 176
Ottenwälder, B., Koldehofe, B., Rothermel, K., & Ramachandran, U. (2013) · ACM International Conference on Distributed and Event-Based Systems (DEBS) · doi:10.1145/2488222.2488265 · Cited by 127
Bousdekis, A., Magoutas, B., Apostolou, D., & Mentzas, G. N. (2015) · Journal of Intelligent Manufacturing · doi:10.1007/s10845-015-1179-5 · Cited by 115
A proactive decision making framework for condition-based maintenance
Bousdekis, A., Magoutas, B., Apostolou, D., & Mentzas, G. N. (2015) · Industrial Management & Data Systems · doi:10.1108/imds-03-2015-0071 · Cited by 109
Metadata
- Authors
- Engel, Y., Etzion, O., & Feldman, Z.
- Affiliations
- IBM Research - Haifa (IL)
- Venue
- Proceedings of the 6th ACM International Conference on Distributed Event-Based Systems
- Publisher
- ACM
- Published
- 2012-07-16
- Pages
- 107-118
- OpenAlex
- W2016575485
- Cited by
- 67
- References
- 22
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 3 · 2023: 2 · 2022: 2 · 2021: 4 · 2020: 2 · 2019: 8 · 2018: 4 · 2017: 7 · 2016: 10 · 2015: 9 · 2014: 8 · 2013: 5 · 2012: 1
- FWCI
- 6.17
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- ACM International Conference on Distributed and Event-Based Systems (DEBS) (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › Advanced Database Systems and Queries
- Physical Sciences › Computer Science › Software › Advanced Software Engineering Methodologies
- Social Sciences › Business, Management and Accounting › Management Information Systems › Business Process Modeling and Analysis
- Keywords
- event processing, proactive agents, event prediction, decision making under uncertainty, condition-based maintenance
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: A basic model for proactive event-driven computing. https://app.cochat.ai/papers/10.1145/2335484.2335496
- The paper
- Engel, Y., Etzion, O., & Feldman, Z. (2012). A basic model for proactive event-driven computing. Proceedings of the 6th ACM International Conference on Distributed Event-Based Systems. https://doi.org/10.1145/2335484.2335496
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
